Deck 4: Basic Estimation Techniques

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Question
In a linear regression equation of the form Y = a + bX, the slope parameter b shows

A) Δ\Delta X / Δ\Delta Y.
B) Δ\Delta Y / Δ\Delta X.
C) Δ\Delta Y / Δ\Delta b.
D) Δ\Delta X / Δ\Delta b.
E) none of the above
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Question
Which of the following is an example of a time-series data set?

A) amount of labor employed in each factory in the U.S. in 2007.
B) amount of labor employed yearly in a specific factory from 1987 through 2007.
C) average amount of labor employed at specific times of the day at a specific factory in 2007.
D) All of the above are time-series data sets.
Question
In the linear model
<strong>In the linear model   , a test of the hypothesis that parameter c equals zero is</strong> A) an F-test. B) an R<sup>2</sup>-test. C) a zero-statistic. D) a t-test. E) a Z-test. <div style=padding-top: 35px>
, a test of the hypothesis that parameter c equals zero is

A) an F-test.
B) an R2-test.
C) a zero-statistic.
D) a t-test.
E) a Z-test.
Question
refer to the following:
The linear regression equation, Y = a + bX, was estimated. The following computer printout was
obtained:
? <strong>refer to the following: The linear regression equation, Y = a + bX, was estimated. The following computer printout was obtained: ?    -What is the critical value of t at the 1% level of significance?</strong> A) 1.746 B) 2.120 C) 2.878 D) 2.921 <div style=padding-top: 35px>

-What is the critical value of t at the 1% level of significance?

A) 1.746
B) 2.120
C) 2.878
D) 2.921
Question
refer to the following:
The linear regression equation, Y = a + bX, was estimated. The following computer printout was
obtained:
? <strong>refer to the following: The linear regression equation, Y = a + bX, was estimated. The following computer printout was obtained: ?    -Which of the following statements is correct at the 1% level of significance?</strong> A) Both   And   Are statistically significant. B) Neither   Nor   Is statistically significant. C)   Is statistically significant, but   Is not. D)   Is statistically significant, but   Is not. <div style=padding-top: 35px>

-Which of the following statements is correct at the 1% level of significance?

A) Both
<strong>refer to the following: The linear regression equation, Y = a + bX, was estimated. The following computer printout was obtained: ?    -Which of the following statements is correct at the 1% level of significance?</strong> A) Both   And   Are statistically significant. B) Neither   Nor   Is statistically significant. C)   Is statistically significant, but   Is not. D)   Is statistically significant, but   Is not. <div style=padding-top: 35px>
And
<strong>refer to the following: The linear regression equation, Y = a + bX, was estimated. The following computer printout was obtained: ?    -Which of the following statements is correct at the 1% level of significance?</strong> A) Both   And   Are statistically significant. B) Neither   Nor   Is statistically significant. C)   Is statistically significant, but   Is not. D)   Is statistically significant, but   Is not. <div style=padding-top: 35px>
Are statistically significant.
B) Neither
<strong>refer to the following: The linear regression equation, Y = a + bX, was estimated. The following computer printout was obtained: ?    -Which of the following statements is correct at the 1% level of significance?</strong> A) Both   And   Are statistically significant. B) Neither   Nor   Is statistically significant. C)   Is statistically significant, but   Is not. D)   Is statistically significant, but   Is not. <div style=padding-top: 35px>
Nor
<strong>refer to the following: The linear regression equation, Y = a + bX, was estimated. The following computer printout was obtained: ?    -Which of the following statements is correct at the 1% level of significance?</strong> A) Both   And   Are statistically significant. B) Neither   Nor   Is statistically significant. C)   Is statistically significant, but   Is not. D)   Is statistically significant, but   Is not. <div style=padding-top: 35px>
Is statistically significant.
C)
<strong>refer to the following: The linear regression equation, Y = a + bX, was estimated. The following computer printout was obtained: ?    -Which of the following statements is correct at the 1% level of significance?</strong> A) Both   And   Are statistically significant. B) Neither   Nor   Is statistically significant. C)   Is statistically significant, but   Is not. D)   Is statistically significant, but   Is not. <div style=padding-top: 35px>
Is statistically significant, but
<strong>refer to the following: The linear regression equation, Y = a + bX, was estimated. The following computer printout was obtained: ?    -Which of the following statements is correct at the 1% level of significance?</strong> A) Both   And   Are statistically significant. B) Neither   Nor   Is statistically significant. C)   Is statistically significant, but   Is not. D)   Is statistically significant, but   Is not. <div style=padding-top: 35px>
Is not.
D)
<strong>refer to the following: The linear regression equation, Y = a + bX, was estimated. The following computer printout was obtained: ?    -Which of the following statements is correct at the 1% level of significance?</strong> A) Both   And   Are statistically significant. B) Neither   Nor   Is statistically significant. C)   Is statistically significant, but   Is not. D)   Is statistically significant, but   Is not. <div style=padding-top: 35px>
Is statistically significant, but
<strong>refer to the following: The linear regression equation, Y = a + bX, was estimated. The following computer printout was obtained: ?    -Which of the following statements is correct at the 1% level of significance?</strong> A) Both   And   Are statistically significant. B) Neither   Nor   Is statistically significant. C)   Is statistically significant, but   Is not. D)   Is statistically significant, but   Is not. <div style=padding-top: 35px>
Is not.
Question
refer to the following:
The linear regression equation, Y = a + bX, was estimated. The following computer printout was
obtained:
? <strong>refer to the following: The linear regression equation, Y = a + bX, was estimated. The following computer printout was obtained: ?    -The exact level of significance of   Is</strong> A) 0.171 percent. B) 1 percent. C) 1.71 percent. D) 2.66 percent. E) 2.921 percent. <div style=padding-top: 35px>

-The exact level of significance of
<strong>refer to the following: The linear regression equation, Y = a + bX, was estimated. The following computer printout was obtained: ?    -The exact level of significance of   Is</strong> A) 0.171 percent. B) 1 percent. C) 1.71 percent. D) 2.66 percent. E) 2.921 percent. <div style=padding-top: 35px>
Is

A) 0.171 percent.
B) 1 percent.
C) 1.71 percent.
D) 2.66 percent.
E) 2.921 percent.
Question
refer to the following:
The linear regression equation, Y = a + bX, was estimated. The following computer printout was
obtained:
? <strong>refer to the following: The linear regression equation, Y = a + bX, was estimated. The following computer printout was obtained: ?    -If X equals 20, what is the predicted value of Y?</strong> A) 186.42 B) 165.69 C) -186.42 D)-411.72 <div style=padding-top: 35px>

-If X equals 20, what is the predicted value of Y?

A) 186.42
B) 165.69
C) -186.42
D)-411.72
Question
refer to the following:
A firm is experiencing theft problems at its warehouse. A consultant to the firm believes that the dollar loss from theft each week (T) depends on the number of security guards (G) and on the unemployment rate in the county where the warehouse is located (U measured as a percent). In order to test this hypothesis, the consultant estimated the regression equation T = a + bG + cU and obtained the following results:
<strong>refer to the following: A firm is experiencing theft problems at its warehouse. A consultant to the firm believes that the dollar loss from theft each week (T) depends on the number of security guards (G) and on the unemployment rate in the county where the warehouse is located (U measured as a percent). In order to test this hypothesis, the consultant estimated the regression equation T = a + bG + cU and obtained the following results:    -Which of the following is correct at the 1% level of significance?</strong> A) The regression equation as a whole is statistically significant because the p-value of F is smaller than 0.01. B) The estimates of the parameters a, b, and c are all statistically significant because the absolute values of their t-ratios exceed 2.797. C) The estimates of the parameters a, b, and c are all statistically significant because the p- values for,   ,   And   Are all less than 0.01. D) The critical value of t is 2.797. E) all of the above <div style=padding-top: 35px>

-Which of the following is correct at the 1% level of significance?

A) The regression equation as a whole is statistically significant because the p-value of F is smaller than 0.01.
B) The estimates of the parameters a, b, and c are all statistically significant because the absolute values of their t-ratios exceed 2.797.
C) The estimates of the parameters a, b, and c are all statistically significant because the p- values for,
<strong>refer to the following: A firm is experiencing theft problems at its warehouse. A consultant to the firm believes that the dollar loss from theft each week (T) depends on the number of security guards (G) and on the unemployment rate in the county where the warehouse is located (U measured as a percent). In order to test this hypothesis, the consultant estimated the regression equation T = a + bG + cU and obtained the following results:    -Which of the following is correct at the 1% level of significance?</strong> A) The regression equation as a whole is statistically significant because the p-value of F is smaller than 0.01. B) The estimates of the parameters a, b, and c are all statistically significant because the absolute values of their t-ratios exceed 2.797. C) The estimates of the parameters a, b, and c are all statistically significant because the p- values for,   ,   And   Are all less than 0.01. D) The critical value of t is 2.797. E) all of the above <div style=padding-top: 35px>
,
<strong>refer to the following: A firm is experiencing theft problems at its warehouse. A consultant to the firm believes that the dollar loss from theft each week (T) depends on the number of security guards (G) and on the unemployment rate in the county where the warehouse is located (U measured as a percent). In order to test this hypothesis, the consultant estimated the regression equation T = a + bG + cU and obtained the following results:    -Which of the following is correct at the 1% level of significance?</strong> A) The regression equation as a whole is statistically significant because the p-value of F is smaller than 0.01. B) The estimates of the parameters a, b, and c are all statistically significant because the absolute values of their t-ratios exceed 2.797. C) The estimates of the parameters a, b, and c are all statistically significant because the p- values for,   ,   And   Are all less than 0.01. D) The critical value of t is 2.797. E) all of the above <div style=padding-top: 35px>
And
<strong>refer to the following: A firm is experiencing theft problems at its warehouse. A consultant to the firm believes that the dollar loss from theft each week (T) depends on the number of security guards (G) and on the unemployment rate in the county where the warehouse is located (U measured as a percent). In order to test this hypothesis, the consultant estimated the regression equation T = a + bG + cU and obtained the following results:    -Which of the following is correct at the 1% level of significance?</strong> A) The regression equation as a whole is statistically significant because the p-value of F is smaller than 0.01. B) The estimates of the parameters a, b, and c are all statistically significant because the absolute values of their t-ratios exceed 2.797. C) The estimates of the parameters a, b, and c are all statistically significant because the p- values for,   ,   And   Are all less than 0.01. D) The critical value of t is 2.797. E) all of the above <div style=padding-top: 35px>
Are all less than 0.01.
D) The critical value of t is 2.797.
E) all of the above
Question
In the nonlinear function
 <strong>In the nonlinear function   , the parameter c measures</strong> A)  \Delta Y / \Delta Z. B) the percent change in Y for a 1 percent change in Z. C) the elasticity of Y with respect to Z. D) both a and c E) both b and c <div style=padding-top: 35px>
, the parameter c measures

A) Δ\Delta Y / Δ\Delta Z.
B) the percent change in Y for a 1 percent change in Z.
C) the elasticity of Y with respect to Z.
D) both a and c
E) both b and c
Question
refer to the following computer output from estimating the parameters of the nonlinear model
<strong>refer to the following computer output from estimating the parameters of the nonlinear model   The computer output from the regression analysis is:    -The nonlinear relation can be transformed into the following linear regression model:</strong> A)   B)   C)   D)   <div style=padding-top: 35px> The computer output from the regression analysis is:
<strong>refer to the following computer output from estimating the parameters of the nonlinear model   The computer output from the regression analysis is:    -The nonlinear relation can be transformed into the following linear regression model:</strong> A)   B)   C)   D)   <div style=padding-top: 35px>

-The nonlinear relation can be transformed into the following linear regression model:

A) <strong>refer to the following computer output from estimating the parameters of the nonlinear model   The computer output from the regression analysis is:    -The nonlinear relation can be transformed into the following linear regression model:</strong> A)   B)   C)   D)   <div style=padding-top: 35px>
B) <strong>refer to the following computer output from estimating the parameters of the nonlinear model   The computer output from the regression analysis is:    -The nonlinear relation can be transformed into the following linear regression model:</strong> A)   B)   C)   D)   <div style=padding-top: 35px>
C) <strong>refer to the following computer output from estimating the parameters of the nonlinear model   The computer output from the regression analysis is:    -The nonlinear relation can be transformed into the following linear regression model:</strong> A)   B)   C)   D)   <div style=padding-top: 35px>
D) <strong>refer to the following computer output from estimating the parameters of the nonlinear model   The computer output from the regression analysis is:    -The nonlinear relation can be transformed into the following linear regression model:</strong> A)   B)   C)   D)   <div style=padding-top: 35px>
Question
refer to the following computer output from estimating the parameters of the nonlinear model
<strong>refer to the following computer output from estimating the parameters of the nonlinear model   The computer output from the regression analysis is:    -The estimated value of a is</strong> A) -0.6931 B) 0.50 C) -3.67 D) 2.66 <div style=padding-top: 35px> The computer output from the regression analysis is:
<strong>refer to the following computer output from estimating the parameters of the nonlinear model   The computer output from the regression analysis is:    -The estimated value of a is</strong> A) -0.6931 B) 0.50 C) -3.67 D) 2.66 <div style=padding-top: 35px>

-The estimated value of a is

A) -0.6931
B) 0.50
C) -3.67
D) 2.66
Question
refer to the following computer output from estimating the parameters of the nonlinear model
<strong>refer to the following computer output from estimating the parameters of the nonlinear model   The computer output from the regression analysis is:    -Which of the parameter estimates are statistically significant at the 90% level of confidence?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   And   Are statistically significant. C)   Is not statistically significant, but all the rest of the parameter estimates are significant. D)   Is not statistically significant, but all the rest of the parameter estimates are significant. <div style=padding-top: 35px> The computer output from the regression analysis is:
<strong>refer to the following computer output from estimating the parameters of the nonlinear model   The computer output from the regression analysis is:    -Which of the parameter estimates are statistically significant at the 90% level of confidence?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   And   Are statistically significant. C)   Is not statistically significant, but all the rest of the parameter estimates are significant. D)   Is not statistically significant, but all the rest of the parameter estimates are significant. <div style=padding-top: 35px>

-Which of the parameter estimates are statistically significant at the 90% level of confidence?

A) All the parameter estimates are statistically significant.
B) All parameter estimates except
<strong>refer to the following computer output from estimating the parameters of the nonlinear model   The computer output from the regression analysis is:    -Which of the parameter estimates are statistically significant at the 90% level of confidence?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   And   Are statistically significant. C)   Is not statistically significant, but all the rest of the parameter estimates are significant. D)   Is not statistically significant, but all the rest of the parameter estimates are significant. <div style=padding-top: 35px>
And
<strong>refer to the following computer output from estimating the parameters of the nonlinear model   The computer output from the regression analysis is:    -Which of the parameter estimates are statistically significant at the 90% level of confidence?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   And   Are statistically significant. C)   Is not statistically significant, but all the rest of the parameter estimates are significant. D)   Is not statistically significant, but all the rest of the parameter estimates are significant. <div style=padding-top: 35px>
Are statistically significant.
C)
<strong>refer to the following computer output from estimating the parameters of the nonlinear model   The computer output from the regression analysis is:    -Which of the parameter estimates are statistically significant at the 90% level of confidence?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   And   Are statistically significant. C)   Is not statistically significant, but all the rest of the parameter estimates are significant. D)   Is not statistically significant, but all the rest of the parameter estimates are significant. <div style=padding-top: 35px>
Is not statistically significant, but all the rest of the parameter estimates are significant.
D)
<strong>refer to the following computer output from estimating the parameters of the nonlinear model   The computer output from the regression analysis is:    -Which of the parameter estimates are statistically significant at the 90% level of confidence?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   And   Are statistically significant. C)   Is not statistically significant, but all the rest of the parameter estimates are significant. D)   Is not statistically significant, but all the rest of the parameter estimates are significant. <div style=padding-top: 35px>
Is not statistically significant, but all the rest of the parameter estimates are significant.
Question
refer to the following nonlinear model which relates W to P, Q, and R:
<strong>refer to the following nonlinear model which relates W to P, Q, and R:   The computer output form the regression analysis is:    -The nonlinear relation can be transformed into the following linear regression model:</strong> A)   B)   C)   D)   <div style=padding-top: 35px>
The computer output form the regression analysis is:
<strong>refer to the following nonlinear model which relates W to P, Q, and R:   The computer output form the regression analysis is:    -The nonlinear relation can be transformed into the following linear regression model:</strong> A)   B)   C)   D)   <div style=padding-top: 35px>

-The nonlinear relation can be transformed into the following linear regression model:

A) <strong>refer to the following nonlinear model which relates W to P, Q, and R:   The computer output form the regression analysis is:    -The nonlinear relation can be transformed into the following linear regression model:</strong> A)   B)   C)   D)   <div style=padding-top: 35px>
B) <strong>refer to the following nonlinear model which relates W to P, Q, and R:   The computer output form the regression analysis is:    -The nonlinear relation can be transformed into the following linear regression model:</strong> A)   B)   C)   D)   <div style=padding-top: 35px>
C) <strong>refer to the following nonlinear model which relates W to P, Q, and R:   The computer output form the regression analysis is:    -The nonlinear relation can be transformed into the following linear regression model:</strong> A)   B)   C)   D)   <div style=padding-top: 35px>
D) <strong>refer to the following nonlinear model which relates W to P, Q, and R:   The computer output form the regression analysis is:    -The nonlinear relation can be transformed into the following linear regression model:</strong> A)   B)   C)   D)   <div style=padding-top: 35px>
Question
refer to the following nonlinear model which relates W to P, Q, and R:
<strong>refer to the following nonlinear model which relates W to P, Q, and R:   The computer output form the regression analysis is:    -Which of the parameter estimates are statistically significant at the 5% level of significance?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   and   are statistically significant. C)   Is not statistically significant, but all the rest of the parameter estimates are significant. D)   Is not statistically significant, but all the rest of the parameter estimates are significant. <div style=padding-top: 35px>
The computer output form the regression analysis is:
<strong>refer to the following nonlinear model which relates W to P, Q, and R:   The computer output form the regression analysis is:    -Which of the parameter estimates are statistically significant at the 5% level of significance?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   and   are statistically significant. C)   Is not statistically significant, but all the rest of the parameter estimates are significant. D)   Is not statistically significant, but all the rest of the parameter estimates are significant. <div style=padding-top: 35px>

-Which of the parameter estimates are statistically significant at the 5% level of significance?

A) All the parameter estimates are statistically significant.
B) All parameter estimates except <strong>refer to the following nonlinear model which relates W to P, Q, and R:   The computer output form the regression analysis is:    -Which of the parameter estimates are statistically significant at the 5% level of significance?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   and   are statistically significant. C)   Is not statistically significant, but all the rest of the parameter estimates are significant. D)   Is not statistically significant, but all the rest of the parameter estimates are significant. <div style=padding-top: 35px> and <strong>refer to the following nonlinear model which relates W to P, Q, and R:   The computer output form the regression analysis is:    -Which of the parameter estimates are statistically significant at the 5% level of significance?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   and   are statistically significant. C)   Is not statistically significant, but all the rest of the parameter estimates are significant. D)   Is not statistically significant, but all the rest of the parameter estimates are significant. <div style=padding-top: 35px> are statistically significant.
C)
<strong>refer to the following nonlinear model which relates W to P, Q, and R:   The computer output form the regression analysis is:    -Which of the parameter estimates are statistically significant at the 5% level of significance?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   and   are statistically significant. C)   Is not statistically significant, but all the rest of the parameter estimates are significant. D)   Is not statistically significant, but all the rest of the parameter estimates are significant. <div style=padding-top: 35px>
Is not statistically significant, but all the rest of the parameter estimates are significant.
D)
<strong>refer to the following nonlinear model which relates W to P, Q, and R:   The computer output form the regression analysis is:    -Which of the parameter estimates are statistically significant at the 5% level of significance?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   and   are statistically significant. C)   Is not statistically significant, but all the rest of the parameter estimates are significant. D)   Is not statistically significant, but all the rest of the parameter estimates are significant. <div style=padding-top: 35px>
Is not statistically significant, but all the rest of the parameter estimates are significant.
Question
refer to the following nonlinear model which relates W to P, Q, and R:
<strong>refer to the following nonlinear model which relates W to P, Q, and R:   The computer output form the regression analysis is:    -The estimated value of a is</strong> A) 0.916 B) 12.182 C) 2.50 D) 2.66 <div style=padding-top: 35px>
The computer output form the regression analysis is:
<strong>refer to the following nonlinear model which relates W to P, Q, and R:   The computer output form the regression analysis is:    -The estimated value of a is</strong> A) 0.916 B) 12.182 C) 2.50 D) 2.66 <div style=padding-top: 35px>

-The estimated value of a is

A) 0.916
B) 12.182
C) 2.50
D) 2.66
Question
In a multiple regression model, the coefficients on the independent variables measure

A) the percent of the variation in the dependent variable explained by a change in that independent variable, all other influences held constant.
B) the change in the dependent variable from a one-unit change in that independent variable, all other influences held constant.
C) the change in that independent variable from a one-unit change in the dependent variable, all other influences held constant.
D) the change in the dependent variable explained by the random error, all other influences held constant.
Question
refer to the following:
A manager wishes to estimate an average cost equation of the following form:
<strong>refer to the following: A manager wishes to estimate an average cost equation of the following form:   where Q is the level of output. Letting Z = Q<sup>2</sup> and using least-squares estimation, the manager obtains the following computer output:    -Which of the parameter estimates are statistically significant at the 1% significance level?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   are statistically significant. C)   is not statistically significant, but all the rest of the parameter estimates are significant. D)   is not statistically significant, but all the rest of the parameter estimates are significant. <div style=padding-top: 35px>
where Q is the level of output. Letting Z = Q2 and using least-squares estimation, the manager obtains the following computer output:
<strong>refer to the following: A manager wishes to estimate an average cost equation of the following form:   where Q is the level of output. Letting Z = Q<sup>2</sup> and using least-squares estimation, the manager obtains the following computer output:    -Which of the parameter estimates are statistically significant at the 1% significance level?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   are statistically significant. C)   is not statistically significant, but all the rest of the parameter estimates are significant. D)   is not statistically significant, but all the rest of the parameter estimates are significant. <div style=padding-top: 35px>

-Which of the parameter estimates are statistically significant at the 1% significance level?

A) All the parameter estimates are statistically significant.
B) All parameter estimates except <strong>refer to the following: A manager wishes to estimate an average cost equation of the following form:   where Q is the level of output. Letting Z = Q<sup>2</sup> and using least-squares estimation, the manager obtains the following computer output:    -Which of the parameter estimates are statistically significant at the 1% significance level?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   are statistically significant. C)   is not statistically significant, but all the rest of the parameter estimates are significant. D)   is not statistically significant, but all the rest of the parameter estimates are significant. <div style=padding-top: 35px> are statistically significant.
C) <strong>refer to the following: A manager wishes to estimate an average cost equation of the following form:   where Q is the level of output. Letting Z = Q<sup>2</sup> and using least-squares estimation, the manager obtains the following computer output:    -Which of the parameter estimates are statistically significant at the 1% significance level?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   are statistically significant. C)   is not statistically significant, but all the rest of the parameter estimates are significant. D)   is not statistically significant, but all the rest of the parameter estimates are significant. <div style=padding-top: 35px> is not statistically significant, but all the rest of the parameter estimates are significant.
D) <strong>refer to the following: A manager wishes to estimate an average cost equation of the following form:   where Q is the level of output. Letting Z = Q<sup>2</sup> and using least-squares estimation, the manager obtains the following computer output:    -Which of the parameter estimates are statistically significant at the 1% significance level?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   are statistically significant. C)   is not statistically significant, but all the rest of the parameter estimates are significant. D)   is not statistically significant, but all the rest of the parameter estimates are significant. <div style=padding-top: 35px> is not statistically significant, but all the rest of the parameter estimates are significant.
Question
refer to the following:
A manager wishes to estimate an average cost equation of the following form:
<strong>refer to the following: A manager wishes to estimate an average cost equation of the following form:   where Q is the level of output. Letting Z = Q<sup>2</sup> and using least-squares estimation, the manager obtains the following computer output:    -When output is 40 units, what is average cost?</strong> A) $200 B) $280 C) $360 D) $480 E) $520 <div style=padding-top: 35px>
where Q is the level of output. Letting Z = Q2 and using least-squares estimation, the manager obtains the following computer output:
<strong>refer to the following: A manager wishes to estimate an average cost equation of the following form:   where Q is the level of output. Letting Z = Q<sup>2</sup> and using least-squares estimation, the manager obtains the following computer output:    -When output is 40 units, what is average cost?</strong> A) $200 B) $280 C) $360 D) $480 E) $520 <div style=padding-top: 35px>

-When output is 40 units, what is average cost?

A) $200
B) $280
C) $360
D) $480
E) $520
Question
refer to the following:
A manager wishes to estimate an average cost equation of the following form:
<strong>refer to the following: A manager wishes to estimate an average cost equation of the following form:   where Q is the level of output. Letting Z = Q<sup>2</sup> and using least-squares estimation, the manager obtains the following computer output:    -When output is 20 units, what is average cost?</strong> A) $160 B) $200 C) $280 D) $340 E) $360 <div style=padding-top: 35px>
where Q is the level of output. Letting Z = Q2 and using least-squares estimation, the manager obtains the following computer output:
<strong>refer to the following: A manager wishes to estimate an average cost equation of the following form:   where Q is the level of output. Letting Z = Q<sup>2</sup> and using least-squares estimation, the manager obtains the following computer output:    -When output is 20 units, what is average cost?</strong> A) $160 B) $200 C) $280 D) $340 E) $360 <div style=padding-top: 35px>

-When output is 20 units, what is average cost?

A) $160
B) $200
C) $280
D) $340
E) $360
Question
A simple linear regression equation relates G and D as follows:
G = a + bD
-The explanatory variable is _______, and the dependent variable is ________.
Question
A simple linear regression equation relates G and D as follows:
G = a + bD
-The slope parameter is ______, and the intercept parameter _______.
Question
A simple linear regression equation relates G and D as follows:
G = a + bD
-When D is zero, G equals _______.
Question
A simple linear regression equation relates G and D as follows:
G = a + bD
-For each one-unit increase in D, the change in R is ______ units.
Question
The linear regression equation G = a + bD is estimated using 24 observations on R and W. The least-squares estimate of b is -22.5, and the standard error of the estimate is 8.36. Perform a t-test for statistical significance of
The linear regression equation G = a + bD is estimated using 24 observations on R and W. The least-squares estimate of b is -22.5, and the standard error of the estimate is 8.36. Perform a t-test for statistical significance of   at the 1% level of significance.  -There are _____ degrees of freedom for the t-test.<div style=padding-top: 35px> at the 1% level of significance.

-There are _____ degrees of freedom for the t-test.
Question
The linear regression equation G = a + bD is estimated using 24 observations on R and W. The least-squares estimate of b is -22.5, and the standard error of the estimate is 8.36. Perform a t-test for statistical significance of
The linear regression equation G = a + bD is estimated using 24 observations on R and W. The least-squares estimate of b is -22.5, and the standard error of the estimate is 8.36. Perform a t-test for statistical significance of   at the 1% level of significance.  -The value of the t-statistic is _________. The critical t-value for the test is _________.<div style=padding-top: 35px> at the 1% level of significance.

-The value of the t-statistic is _________. The critical t-value for the test is _________.
Question
The linear regression equation G = a + bD is estimated using 24 observations on R and W. The least-squares estimate of b is -22.5, and the standard error of the estimate is 8.36. Perform a t-test for statistical significance of
The linear regression equation G = a + bD is estimated using 24 observations on R and W. The least-squares estimate of b is -22.5, and the standard error of the estimate is 8.36. Perform a t-test for statistical significance of   at the 1% level of significance.  -The parameter estimate _________ (is, is not) statistically significant at the 1% level.<div style=padding-top: 35px> at the 1% level of significance.

-The parameter estimate _________ (is, is not) statistically significant at the 1% level.
Question
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is    -The equation of the sample regression line is: = __________________________.<div style=padding-top: 35px>

-The equation of the sample regression line is: = __________________________.
Question
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is    -There are ______ degrees of freedom for the t-test. At the 5% level of significance, the critical t-value for the test is ______________.<div style=padding-top: 35px>

-There are ______ degrees of freedom for the t-test. At the 5% level of significance, the critical t-value for the test is ______________.
Question
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is    -At the 5% level of significance, __________ (is, not) significant, and ________ (is, is not) significant.<div style=padding-top: 35px>

-At the 5% level of significance, __________ (is, not) significant, and ________ (is, is not) significant.
Question
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is    -At the 2% level of significance, the critical t-value for a t-test is ___________. At the 2% level of significance, _________ (is, is not) significant, and _________ (is, is not) significant.<div style=padding-top: 35px>

-At the 2% level of significance, the critical t-value for a t-test is ___________. At the 2% level of significance, _________ (is, is not) significant, and _________ (is, is not) significant.
Question
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is    -The p-value for indicates that the exact level of significance is ______ percent, which is the probability of _________________________________________.<div style=padding-top: 35px>

-The p-value for indicates that the exact level of significance is ______ percent, which is the probability of _________________________________________.
Question
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is    -At the 5% level of significance, the critical value of the F-statistic is _______. The model as a whole ___________(is, is not) significant at the 5% level.<div style=padding-top: 35px>

-At the 5% level of significance, the critical value of the F-statistic is _______. The model as a whole ___________(is, is not) significant at the 5% level.
Question
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is    -If X equals 240, the fitted (or predicted) value of Y is ____________________________.<div style=padding-top: 35px>

-If X equals 240, the fitted (or predicted) value of Y is ____________________________.
Question
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is    -The percentage of the total variation in Y that is NOT explained by the regression is ________.<div style=padding-top: 35px>

-The percentage of the total variation in Y that is NOT explained by the regression is ________.
Question
4-4F Suppose Y is related to R and S in the following nonlinear way:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -In order to estimate the parameters a, b, and c, the equation must be transformed into the form: ___________________________________.<div style=padding-top: 35px>
Twenty-six observations are used to obtain the following regression results:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -In order to estimate the parameters a, b, and c, the equation must be transformed into the form: ___________________________________.<div style=padding-top: 35px>
-In order to estimate the parameters a, b, and c, the equation must be transformed into the form: ___________________________________.
Question
4-4F Suppose Y is related to R and S in the following nonlinear way:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -There are _______ degrees of freedom for the t-test. At the 1% level of significance, the critical t-value for the test is __________.<div style=padding-top: 35px>
Twenty-six observations are used to obtain the following regression results:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -There are _______ degrees of freedom for the t-test. At the 1% level of significance, the critical t-value for the test is __________.<div style=padding-top: 35px>
-There are _______ degrees of freedom for the t-test. At the 1% level of significance, the critical t-value for the test is __________.
Question
4-4F Suppose Y is related to R and S in the following nonlinear way:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -At the 1% level of significance, _______ (is, is not) significant, _______ (is, is not) significant, and ________ (is, is not) significant.<div style=padding-top: 35px>
Twenty-six observations are used to obtain the following regression results:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -At the 1% level of significance, _______ (is, is not) significant, _______ (is, is not) significant, and ________ (is, is not) significant.<div style=padding-top: 35px>
-At the 1% level of significance, _______ (is, is not) significant, _______ (is, is not) significant, and ________ (is, is not) significant.
Question
4-4F Suppose Y is related to R and S in the following nonlinear way:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -The estimated value of a is ______________.<div style=padding-top: 35px>
Twenty-six observations are used to obtain the following regression results:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -The estimated value of a is ______________.<div style=padding-top: 35px>
-The estimated value of a is ______________.
Question
4-4F Suppose Y is related to R and S in the following nonlinear way:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -The p-value for indicates that the exact level of significance is _________ percent, which is the probability of _________________.<div style=padding-top: 35px>
Twenty-six observations are used to obtain the following regression results:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -The p-value for indicates that the exact level of significance is _________ percent, which is the probability of _________________.<div style=padding-top: 35px>
-The p-value for indicates that the exact level of significance is _________ percent, which is the probability of _________________.
Question
4-4F Suppose Y is related to R and S in the following nonlinear way:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -At the 1% level of significance, the critical value of the F-statistic is _________. The model as a whole _________ (is, is not) significant at the 1% level.<div style=padding-top: 35px>
Twenty-six observations are used to obtain the following regression results:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -At the 1% level of significance, the critical value of the F-statistic is _________. The model as a whole _________ (is, is not) significant at the 1% level.<div style=padding-top: 35px>
-At the 1% level of significance, the critical value of the F-statistic is _________. The model as a whole _________ (is, is not) significant at the 1% level.
Question
4-4F Suppose Y is related to R and S in the following nonlinear way:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -If R equals 12 and S equals 30, the fitted (or predicted) value of Y is _____________.<div style=padding-top: 35px>
Twenty-six observations are used to obtain the following regression results:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -If R equals 12 and S equals 30, the fitted (or predicted) value of Y is _____________.<div style=padding-top: 35px>
-If R equals 12 and S equals 30, the fitted (or predicted) value of Y is _____________.
Question
4-4F Suppose Y is related to R and S in the following nonlinear way:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -The percentage of the total variation in the dependent variable NOT explained by the regression is _______________.<div style=padding-top: 35px>
Twenty-six observations are used to obtain the following regression results:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -The percentage of the total variation in the dependent variable NOT explained by the regression is _______________.<div style=padding-top: 35px>
-The percentage of the total variation in the dependent variable NOT explained by the regression is _______________.
Question
4-4F Suppose Y is related to R and S in the following nonlinear way:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -If R increases by 14%, Y will increase by ________ percent.<div style=padding-top: 35px>
Twenty-six observations are used to obtain the following regression results:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -If R increases by 14%, Y will increase by ________ percent.<div style=padding-top: 35px>
-If R increases by 14%, Y will increase by ________ percent.
Question
4-4F Suppose Y is related to R and S in the following nonlinear way:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -A 6.87% increase in Y will occur if S ________________ (increases, decreases) by _______ percent.<div style=padding-top: 35px>
Twenty-six observations are used to obtain the following regression results:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -A 6.87% increase in Y will occur if S ________________ (increases, decreases) by _______ percent.<div style=padding-top: 35px>
-A 6.87% increase in Y will occur if S ________________ (increases, decreases) by _______ percent.
Question
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -The estimated sample regression line is _________________________________.<div style=padding-top: 35px> . The computer output from the regression analysis is shown below:
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -The estimated sample regression line is _________________________________.<div style=padding-top: 35px>
-The estimated sample regression line is _________________________________.
Question
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -At the 2% level of significance, ‪   _________ (is, is NOT) significant,‪   _________ (is, is NOT) significant,‪   _________ (is, is NOT) significant, and‪   _________ (is, is NOT) significant.<div style=padding-top: 35px> . The computer output from the regression analysis is shown below:
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -At the 2% level of significance, ‪   _________ (is, is NOT) significant,‪   _________ (is, is NOT) significant,‪   _________ (is, is NOT) significant, and‪   _________ (is, is NOT) significant.<div style=padding-top: 35px>
-At the 2% level of significance, ‪ 4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -At the 2% level of significance, ‪   _________ (is, is NOT) significant,‪   _________ (is, is NOT) significant,‪   _________ (is, is NOT) significant, and‪   _________ (is, is NOT) significant.<div style=padding-top: 35px> _________ (is, is NOT) significant,‪ 4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -At the 2% level of significance, ‪   _________ (is, is NOT) significant,‪   _________ (is, is NOT) significant,‪   _________ (is, is NOT) significant, and‪   _________ (is, is NOT) significant.<div style=padding-top: 35px> _________ (is, is NOT) significant,‪ 4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -At the 2% level of significance, ‪   _________ (is, is NOT) significant,‪   _________ (is, is NOT) significant,‪   _________ (is, is NOT) significant, and‪   _________ (is, is NOT) significant.<div style=padding-top: 35px> _________ (is, is NOT) significant, and‪ 4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -At the 2% level of significance, ‪   _________ (is, is NOT) significant,‪   _________ (is, is NOT) significant,‪   _________ (is, is NOT) significant, and‪   _________ (is, is NOT) significant.<div style=padding-top: 35px> _________ (is, is NOT) significant.
Question
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -At the 4% level of significance,   __________ (is, is not) significant,   ________ (is, is not) significant,   ________ (is, is not) significant, and   ________ (is, is not) significant.<div style=padding-top: 35px> . The computer output from the regression analysis is shown below:
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -At the 4% level of significance,   __________ (is, is not) significant,   ________ (is, is not) significant,   ________ (is, is not) significant, and   ________ (is, is not) significant.<div style=padding-top: 35px>
-At the 4% level of significance, 4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -At the 4% level of significance,   __________ (is, is not) significant,   ________ (is, is not) significant,   ________ (is, is not) significant, and   ________ (is, is not) significant.<div style=padding-top: 35px> __________ (is, is not) significant, 4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -At the 4% level of significance,   __________ (is, is not) significant,   ________ (is, is not) significant,   ________ (is, is not) significant, and   ________ (is, is not) significant.<div style=padding-top: 35px> ________ (is, is not) significant, 4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -At the 4% level of significance,   __________ (is, is not) significant,   ________ (is, is not) significant,   ________ (is, is not) significant, and   ________ (is, is not) significant.<div style=padding-top: 35px> ________ (is, is not) significant, and 4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -At the 4% level of significance,   __________ (is, is not) significant,   ________ (is, is not) significant,   ________ (is, is not) significant, and   ________ (is, is not) significant.<div style=padding-top: 35px> ________ (is, is not) significant.
Question
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -The p-value for indicates that the exact level of significance is ______ percent, which is the probability of _______________________________.<div style=padding-top: 35px> . The computer output from the regression analysis is shown below:
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -The p-value for indicates that the exact level of significance is ______ percent, which is the probability of _______________________________.<div style=padding-top: 35px>
-The p-value for indicates that the exact level of significance is ______ percent, which is the probability of _______________________________.
Question
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -If U equals 4, V equals 8, and W equals 10, the fitted (or predicted) value of H is ____________.<div style=padding-top: 35px> . The computer output from the regression analysis is shown below:
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -If U equals 4, V equals 8, and W equals 10, the fitted (or predicted) value of H is ____________.<div style=padding-top: 35px>
-If U equals 4, V equals 8, and W equals 10, the fitted (or predicted) value of H is ____________.
Question
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -The percentage of the total variation in H explained by the regression is ________ percent.<div style=padding-top: 35px> . The computer output from the regression analysis is shown below:
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -The percentage of the total variation in H explained by the regression is ________ percent.<div style=padding-top: 35px>
-The percentage of the total variation in H explained by the regression is ________ percent.
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Deck 4: Basic Estimation Techniques
1
In a linear regression equation of the form Y = a + bX, the slope parameter b shows

A) Δ\Delta X / Δ\Delta Y.
B) Δ\Delta Y / Δ\Delta X.
C) Δ\Delta Y / Δ\Delta b.
D) Δ\Delta X / Δ\Delta b.
E) none of the above
Δ\Delta Y / Δ\Delta X.
2
Which of the following is an example of a time-series data set?

A) amount of labor employed in each factory in the U.S. in 2007.
B) amount of labor employed yearly in a specific factory from 1987 through 2007.
C) average amount of labor employed at specific times of the day at a specific factory in 2007.
D) All of the above are time-series data sets.
amount of labor employed yearly in a specific factory from 1987 through 2007.
3
In the linear model
<strong>In the linear model   , a test of the hypothesis that parameter c equals zero is</strong> A) an F-test. B) an R<sup>2</sup>-test. C) a zero-statistic. D) a t-test. E) a Z-test.
, a test of the hypothesis that parameter c equals zero is

A) an F-test.
B) an R2-test.
C) a zero-statistic.
D) a t-test.
E) a Z-test.
a t-test.
4
refer to the following:
The linear regression equation, Y = a + bX, was estimated. The following computer printout was
obtained:
? <strong>refer to the following: The linear regression equation, Y = a + bX, was estimated. The following computer printout was obtained: ?    -What is the critical value of t at the 1% level of significance?</strong> A) 1.746 B) 2.120 C) 2.878 D) 2.921

-What is the critical value of t at the 1% level of significance?

A) 1.746
B) 2.120
C) 2.878
D) 2.921
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5
refer to the following:
The linear regression equation, Y = a + bX, was estimated. The following computer printout was
obtained:
? <strong>refer to the following: The linear regression equation, Y = a + bX, was estimated. The following computer printout was obtained: ?    -Which of the following statements is correct at the 1% level of significance?</strong> A) Both   And   Are statistically significant. B) Neither   Nor   Is statistically significant. C)   Is statistically significant, but   Is not. D)   Is statistically significant, but   Is not.

-Which of the following statements is correct at the 1% level of significance?

A) Both
<strong>refer to the following: The linear regression equation, Y = a + bX, was estimated. The following computer printout was obtained: ?    -Which of the following statements is correct at the 1% level of significance?</strong> A) Both   And   Are statistically significant. B) Neither   Nor   Is statistically significant. C)   Is statistically significant, but   Is not. D)   Is statistically significant, but   Is not.
And
<strong>refer to the following: The linear regression equation, Y = a + bX, was estimated. The following computer printout was obtained: ?    -Which of the following statements is correct at the 1% level of significance?</strong> A) Both   And   Are statistically significant. B) Neither   Nor   Is statistically significant. C)   Is statistically significant, but   Is not. D)   Is statistically significant, but   Is not.
Are statistically significant.
B) Neither
<strong>refer to the following: The linear regression equation, Y = a + bX, was estimated. The following computer printout was obtained: ?    -Which of the following statements is correct at the 1% level of significance?</strong> A) Both   And   Are statistically significant. B) Neither   Nor   Is statistically significant. C)   Is statistically significant, but   Is not. D)   Is statistically significant, but   Is not.
Nor
<strong>refer to the following: The linear regression equation, Y = a + bX, was estimated. The following computer printout was obtained: ?    -Which of the following statements is correct at the 1% level of significance?</strong> A) Both   And   Are statistically significant. B) Neither   Nor   Is statistically significant. C)   Is statistically significant, but   Is not. D)   Is statistically significant, but   Is not.
Is statistically significant.
C)
<strong>refer to the following: The linear regression equation, Y = a + bX, was estimated. The following computer printout was obtained: ?    -Which of the following statements is correct at the 1% level of significance?</strong> A) Both   And   Are statistically significant. B) Neither   Nor   Is statistically significant. C)   Is statistically significant, but   Is not. D)   Is statistically significant, but   Is not.
Is statistically significant, but
<strong>refer to the following: The linear regression equation, Y = a + bX, was estimated. The following computer printout was obtained: ?    -Which of the following statements is correct at the 1% level of significance?</strong> A) Both   And   Are statistically significant. B) Neither   Nor   Is statistically significant. C)   Is statistically significant, but   Is not. D)   Is statistically significant, but   Is not.
Is not.
D)
<strong>refer to the following: The linear regression equation, Y = a + bX, was estimated. The following computer printout was obtained: ?    -Which of the following statements is correct at the 1% level of significance?</strong> A) Both   And   Are statistically significant. B) Neither   Nor   Is statistically significant. C)   Is statistically significant, but   Is not. D)   Is statistically significant, but   Is not.
Is statistically significant, but
<strong>refer to the following: The linear regression equation, Y = a + bX, was estimated. The following computer printout was obtained: ?    -Which of the following statements is correct at the 1% level of significance?</strong> A) Both   And   Are statistically significant. B) Neither   Nor   Is statistically significant. C)   Is statistically significant, but   Is not. D)   Is statistically significant, but   Is not.
Is not.
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6
refer to the following:
The linear regression equation, Y = a + bX, was estimated. The following computer printout was
obtained:
? <strong>refer to the following: The linear regression equation, Y = a + bX, was estimated. The following computer printout was obtained: ?    -The exact level of significance of   Is</strong> A) 0.171 percent. B) 1 percent. C) 1.71 percent. D) 2.66 percent. E) 2.921 percent.

-The exact level of significance of
<strong>refer to the following: The linear regression equation, Y = a + bX, was estimated. The following computer printout was obtained: ?    -The exact level of significance of   Is</strong> A) 0.171 percent. B) 1 percent. C) 1.71 percent. D) 2.66 percent. E) 2.921 percent.
Is

A) 0.171 percent.
B) 1 percent.
C) 1.71 percent.
D) 2.66 percent.
E) 2.921 percent.
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7
refer to the following:
The linear regression equation, Y = a + bX, was estimated. The following computer printout was
obtained:
? <strong>refer to the following: The linear regression equation, Y = a + bX, was estimated. The following computer printout was obtained: ?    -If X equals 20, what is the predicted value of Y?</strong> A) 186.42 B) 165.69 C) -186.42 D)-411.72

-If X equals 20, what is the predicted value of Y?

A) 186.42
B) 165.69
C) -186.42
D)-411.72
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8
refer to the following:
A firm is experiencing theft problems at its warehouse. A consultant to the firm believes that the dollar loss from theft each week (T) depends on the number of security guards (G) and on the unemployment rate in the county where the warehouse is located (U measured as a percent). In order to test this hypothesis, the consultant estimated the regression equation T = a + bG + cU and obtained the following results:
<strong>refer to the following: A firm is experiencing theft problems at its warehouse. A consultant to the firm believes that the dollar loss from theft each week (T) depends on the number of security guards (G) and on the unemployment rate in the county where the warehouse is located (U measured as a percent). In order to test this hypothesis, the consultant estimated the regression equation T = a + bG + cU and obtained the following results:    -Which of the following is correct at the 1% level of significance?</strong> A) The regression equation as a whole is statistically significant because the p-value of F is smaller than 0.01. B) The estimates of the parameters a, b, and c are all statistically significant because the absolute values of their t-ratios exceed 2.797. C) The estimates of the parameters a, b, and c are all statistically significant because the p- values for,   ,   And   Are all less than 0.01. D) The critical value of t is 2.797. E) all of the above

-Which of the following is correct at the 1% level of significance?

A) The regression equation as a whole is statistically significant because the p-value of F is smaller than 0.01.
B) The estimates of the parameters a, b, and c are all statistically significant because the absolute values of their t-ratios exceed 2.797.
C) The estimates of the parameters a, b, and c are all statistically significant because the p- values for,
<strong>refer to the following: A firm is experiencing theft problems at its warehouse. A consultant to the firm believes that the dollar loss from theft each week (T) depends on the number of security guards (G) and on the unemployment rate in the county where the warehouse is located (U measured as a percent). In order to test this hypothesis, the consultant estimated the regression equation T = a + bG + cU and obtained the following results:    -Which of the following is correct at the 1% level of significance?</strong> A) The regression equation as a whole is statistically significant because the p-value of F is smaller than 0.01. B) The estimates of the parameters a, b, and c are all statistically significant because the absolute values of their t-ratios exceed 2.797. C) The estimates of the parameters a, b, and c are all statistically significant because the p- values for,   ,   And   Are all less than 0.01. D) The critical value of t is 2.797. E) all of the above
,
<strong>refer to the following: A firm is experiencing theft problems at its warehouse. A consultant to the firm believes that the dollar loss from theft each week (T) depends on the number of security guards (G) and on the unemployment rate in the county where the warehouse is located (U measured as a percent). In order to test this hypothesis, the consultant estimated the regression equation T = a + bG + cU and obtained the following results:    -Which of the following is correct at the 1% level of significance?</strong> A) The regression equation as a whole is statistically significant because the p-value of F is smaller than 0.01. B) The estimates of the parameters a, b, and c are all statistically significant because the absolute values of their t-ratios exceed 2.797. C) The estimates of the parameters a, b, and c are all statistically significant because the p- values for,   ,   And   Are all less than 0.01. D) The critical value of t is 2.797. E) all of the above
And
<strong>refer to the following: A firm is experiencing theft problems at its warehouse. A consultant to the firm believes that the dollar loss from theft each week (T) depends on the number of security guards (G) and on the unemployment rate in the county where the warehouse is located (U measured as a percent). In order to test this hypothesis, the consultant estimated the regression equation T = a + bG + cU and obtained the following results:    -Which of the following is correct at the 1% level of significance?</strong> A) The regression equation as a whole is statistically significant because the p-value of F is smaller than 0.01. B) The estimates of the parameters a, b, and c are all statistically significant because the absolute values of their t-ratios exceed 2.797. C) The estimates of the parameters a, b, and c are all statistically significant because the p- values for,   ,   And   Are all less than 0.01. D) The critical value of t is 2.797. E) all of the above
Are all less than 0.01.
D) The critical value of t is 2.797.
E) all of the above
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9
In the nonlinear function
 <strong>In the nonlinear function   , the parameter c measures</strong> A)  \Delta Y / \Delta Z. B) the percent change in Y for a 1 percent change in Z. C) the elasticity of Y with respect to Z. D) both a and c E) both b and c
, the parameter c measures

A) Δ\Delta Y / Δ\Delta Z.
B) the percent change in Y for a 1 percent change in Z.
C) the elasticity of Y with respect to Z.
D) both a and c
E) both b and c
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10
refer to the following computer output from estimating the parameters of the nonlinear model
<strong>refer to the following computer output from estimating the parameters of the nonlinear model   The computer output from the regression analysis is:    -The nonlinear relation can be transformed into the following linear regression model:</strong> A)   B)   C)   D)   The computer output from the regression analysis is:
<strong>refer to the following computer output from estimating the parameters of the nonlinear model   The computer output from the regression analysis is:    -The nonlinear relation can be transformed into the following linear regression model:</strong> A)   B)   C)   D)

-The nonlinear relation can be transformed into the following linear regression model:

A) <strong>refer to the following computer output from estimating the parameters of the nonlinear model   The computer output from the regression analysis is:    -The nonlinear relation can be transformed into the following linear regression model:</strong> A)   B)   C)   D)
B) <strong>refer to the following computer output from estimating the parameters of the nonlinear model   The computer output from the regression analysis is:    -The nonlinear relation can be transformed into the following linear regression model:</strong> A)   B)   C)   D)
C) <strong>refer to the following computer output from estimating the parameters of the nonlinear model   The computer output from the regression analysis is:    -The nonlinear relation can be transformed into the following linear regression model:</strong> A)   B)   C)   D)
D) <strong>refer to the following computer output from estimating the parameters of the nonlinear model   The computer output from the regression analysis is:    -The nonlinear relation can be transformed into the following linear regression model:</strong> A)   B)   C)   D)
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11
refer to the following computer output from estimating the parameters of the nonlinear model
<strong>refer to the following computer output from estimating the parameters of the nonlinear model   The computer output from the regression analysis is:    -The estimated value of a is</strong> A) -0.6931 B) 0.50 C) -3.67 D) 2.66 The computer output from the regression analysis is:
<strong>refer to the following computer output from estimating the parameters of the nonlinear model   The computer output from the regression analysis is:    -The estimated value of a is</strong> A) -0.6931 B) 0.50 C) -3.67 D) 2.66

-The estimated value of a is

A) -0.6931
B) 0.50
C) -3.67
D) 2.66
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12
refer to the following computer output from estimating the parameters of the nonlinear model
<strong>refer to the following computer output from estimating the parameters of the nonlinear model   The computer output from the regression analysis is:    -Which of the parameter estimates are statistically significant at the 90% level of confidence?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   And   Are statistically significant. C)   Is not statistically significant, but all the rest of the parameter estimates are significant. D)   Is not statistically significant, but all the rest of the parameter estimates are significant. The computer output from the regression analysis is:
<strong>refer to the following computer output from estimating the parameters of the nonlinear model   The computer output from the regression analysis is:    -Which of the parameter estimates are statistically significant at the 90% level of confidence?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   And   Are statistically significant. C)   Is not statistically significant, but all the rest of the parameter estimates are significant. D)   Is not statistically significant, but all the rest of the parameter estimates are significant.

-Which of the parameter estimates are statistically significant at the 90% level of confidence?

A) All the parameter estimates are statistically significant.
B) All parameter estimates except
<strong>refer to the following computer output from estimating the parameters of the nonlinear model   The computer output from the regression analysis is:    -Which of the parameter estimates are statistically significant at the 90% level of confidence?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   And   Are statistically significant. C)   Is not statistically significant, but all the rest of the parameter estimates are significant. D)   Is not statistically significant, but all the rest of the parameter estimates are significant.
And
<strong>refer to the following computer output from estimating the parameters of the nonlinear model   The computer output from the regression analysis is:    -Which of the parameter estimates are statistically significant at the 90% level of confidence?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   And   Are statistically significant. C)   Is not statistically significant, but all the rest of the parameter estimates are significant. D)   Is not statistically significant, but all the rest of the parameter estimates are significant.
Are statistically significant.
C)
<strong>refer to the following computer output from estimating the parameters of the nonlinear model   The computer output from the regression analysis is:    -Which of the parameter estimates are statistically significant at the 90% level of confidence?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   And   Are statistically significant. C)   Is not statistically significant, but all the rest of the parameter estimates are significant. D)   Is not statistically significant, but all the rest of the parameter estimates are significant.
Is not statistically significant, but all the rest of the parameter estimates are significant.
D)
<strong>refer to the following computer output from estimating the parameters of the nonlinear model   The computer output from the regression analysis is:    -Which of the parameter estimates are statistically significant at the 90% level of confidence?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   And   Are statistically significant. C)   Is not statistically significant, but all the rest of the parameter estimates are significant. D)   Is not statistically significant, but all the rest of the parameter estimates are significant.
Is not statistically significant, but all the rest of the parameter estimates are significant.
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13
refer to the following nonlinear model which relates W to P, Q, and R:
<strong>refer to the following nonlinear model which relates W to P, Q, and R:   The computer output form the regression analysis is:    -The nonlinear relation can be transformed into the following linear regression model:</strong> A)   B)   C)   D)
The computer output form the regression analysis is:
<strong>refer to the following nonlinear model which relates W to P, Q, and R:   The computer output form the regression analysis is:    -The nonlinear relation can be transformed into the following linear regression model:</strong> A)   B)   C)   D)

-The nonlinear relation can be transformed into the following linear regression model:

A) <strong>refer to the following nonlinear model which relates W to P, Q, and R:   The computer output form the regression analysis is:    -The nonlinear relation can be transformed into the following linear regression model:</strong> A)   B)   C)   D)
B) <strong>refer to the following nonlinear model which relates W to P, Q, and R:   The computer output form the regression analysis is:    -The nonlinear relation can be transformed into the following linear regression model:</strong> A)   B)   C)   D)
C) <strong>refer to the following nonlinear model which relates W to P, Q, and R:   The computer output form the regression analysis is:    -The nonlinear relation can be transformed into the following linear regression model:</strong> A)   B)   C)   D)
D) <strong>refer to the following nonlinear model which relates W to P, Q, and R:   The computer output form the regression analysis is:    -The nonlinear relation can be transformed into the following linear regression model:</strong> A)   B)   C)   D)
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14
refer to the following nonlinear model which relates W to P, Q, and R:
<strong>refer to the following nonlinear model which relates W to P, Q, and R:   The computer output form the regression analysis is:    -Which of the parameter estimates are statistically significant at the 5% level of significance?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   and   are statistically significant. C)   Is not statistically significant, but all the rest of the parameter estimates are significant. D)   Is not statistically significant, but all the rest of the parameter estimates are significant.
The computer output form the regression analysis is:
<strong>refer to the following nonlinear model which relates W to P, Q, and R:   The computer output form the regression analysis is:    -Which of the parameter estimates are statistically significant at the 5% level of significance?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   and   are statistically significant. C)   Is not statistically significant, but all the rest of the parameter estimates are significant. D)   Is not statistically significant, but all the rest of the parameter estimates are significant.

-Which of the parameter estimates are statistically significant at the 5% level of significance?

A) All the parameter estimates are statistically significant.
B) All parameter estimates except <strong>refer to the following nonlinear model which relates W to P, Q, and R:   The computer output form the regression analysis is:    -Which of the parameter estimates are statistically significant at the 5% level of significance?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   and   are statistically significant. C)   Is not statistically significant, but all the rest of the parameter estimates are significant. D)   Is not statistically significant, but all the rest of the parameter estimates are significant. and <strong>refer to the following nonlinear model which relates W to P, Q, and R:   The computer output form the regression analysis is:    -Which of the parameter estimates are statistically significant at the 5% level of significance?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   and   are statistically significant. C)   Is not statistically significant, but all the rest of the parameter estimates are significant. D)   Is not statistically significant, but all the rest of the parameter estimates are significant. are statistically significant.
C)
<strong>refer to the following nonlinear model which relates W to P, Q, and R:   The computer output form the regression analysis is:    -Which of the parameter estimates are statistically significant at the 5% level of significance?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   and   are statistically significant. C)   Is not statistically significant, but all the rest of the parameter estimates are significant. D)   Is not statistically significant, but all the rest of the parameter estimates are significant.
Is not statistically significant, but all the rest of the parameter estimates are significant.
D)
<strong>refer to the following nonlinear model which relates W to P, Q, and R:   The computer output form the regression analysis is:    -Which of the parameter estimates are statistically significant at the 5% level of significance?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   and   are statistically significant. C)   Is not statistically significant, but all the rest of the parameter estimates are significant. D)   Is not statistically significant, but all the rest of the parameter estimates are significant.
Is not statistically significant, but all the rest of the parameter estimates are significant.
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15
refer to the following nonlinear model which relates W to P, Q, and R:
<strong>refer to the following nonlinear model which relates W to P, Q, and R:   The computer output form the regression analysis is:    -The estimated value of a is</strong> A) 0.916 B) 12.182 C) 2.50 D) 2.66
The computer output form the regression analysis is:
<strong>refer to the following nonlinear model which relates W to P, Q, and R:   The computer output form the regression analysis is:    -The estimated value of a is</strong> A) 0.916 B) 12.182 C) 2.50 D) 2.66

-The estimated value of a is

A) 0.916
B) 12.182
C) 2.50
D) 2.66
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16
In a multiple regression model, the coefficients on the independent variables measure

A) the percent of the variation in the dependent variable explained by a change in that independent variable, all other influences held constant.
B) the change in the dependent variable from a one-unit change in that independent variable, all other influences held constant.
C) the change in that independent variable from a one-unit change in the dependent variable, all other influences held constant.
D) the change in the dependent variable explained by the random error, all other influences held constant.
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17
refer to the following:
A manager wishes to estimate an average cost equation of the following form:
<strong>refer to the following: A manager wishes to estimate an average cost equation of the following form:   where Q is the level of output. Letting Z = Q<sup>2</sup> and using least-squares estimation, the manager obtains the following computer output:    -Which of the parameter estimates are statistically significant at the 1% significance level?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   are statistically significant. C)   is not statistically significant, but all the rest of the parameter estimates are significant. D)   is not statistically significant, but all the rest of the parameter estimates are significant.
where Q is the level of output. Letting Z = Q2 and using least-squares estimation, the manager obtains the following computer output:
<strong>refer to the following: A manager wishes to estimate an average cost equation of the following form:   where Q is the level of output. Letting Z = Q<sup>2</sup> and using least-squares estimation, the manager obtains the following computer output:    -Which of the parameter estimates are statistically significant at the 1% significance level?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   are statistically significant. C)   is not statistically significant, but all the rest of the parameter estimates are significant. D)   is not statistically significant, but all the rest of the parameter estimates are significant.

-Which of the parameter estimates are statistically significant at the 1% significance level?

A) All the parameter estimates are statistically significant.
B) All parameter estimates except <strong>refer to the following: A manager wishes to estimate an average cost equation of the following form:   where Q is the level of output. Letting Z = Q<sup>2</sup> and using least-squares estimation, the manager obtains the following computer output:    -Which of the parameter estimates are statistically significant at the 1% significance level?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   are statistically significant. C)   is not statistically significant, but all the rest of the parameter estimates are significant. D)   is not statistically significant, but all the rest of the parameter estimates are significant. are statistically significant.
C) <strong>refer to the following: A manager wishes to estimate an average cost equation of the following form:   where Q is the level of output. Letting Z = Q<sup>2</sup> and using least-squares estimation, the manager obtains the following computer output:    -Which of the parameter estimates are statistically significant at the 1% significance level?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   are statistically significant. C)   is not statistically significant, but all the rest of the parameter estimates are significant. D)   is not statistically significant, but all the rest of the parameter estimates are significant. is not statistically significant, but all the rest of the parameter estimates are significant.
D) <strong>refer to the following: A manager wishes to estimate an average cost equation of the following form:   where Q is the level of output. Letting Z = Q<sup>2</sup> and using least-squares estimation, the manager obtains the following computer output:    -Which of the parameter estimates are statistically significant at the 1% significance level?</strong> A) All the parameter estimates are statistically significant. B) All parameter estimates except   are statistically significant. C)   is not statistically significant, but all the rest of the parameter estimates are significant. D)   is not statistically significant, but all the rest of the parameter estimates are significant. is not statistically significant, but all the rest of the parameter estimates are significant.
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18
refer to the following:
A manager wishes to estimate an average cost equation of the following form:
<strong>refer to the following: A manager wishes to estimate an average cost equation of the following form:   where Q is the level of output. Letting Z = Q<sup>2</sup> and using least-squares estimation, the manager obtains the following computer output:    -When output is 40 units, what is average cost?</strong> A) $200 B) $280 C) $360 D) $480 E) $520
where Q is the level of output. Letting Z = Q2 and using least-squares estimation, the manager obtains the following computer output:
<strong>refer to the following: A manager wishes to estimate an average cost equation of the following form:   where Q is the level of output. Letting Z = Q<sup>2</sup> and using least-squares estimation, the manager obtains the following computer output:    -When output is 40 units, what is average cost?</strong> A) $200 B) $280 C) $360 D) $480 E) $520

-When output is 40 units, what is average cost?

A) $200
B) $280
C) $360
D) $480
E) $520
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19
refer to the following:
A manager wishes to estimate an average cost equation of the following form:
<strong>refer to the following: A manager wishes to estimate an average cost equation of the following form:   where Q is the level of output. Letting Z = Q<sup>2</sup> and using least-squares estimation, the manager obtains the following computer output:    -When output is 20 units, what is average cost?</strong> A) $160 B) $200 C) $280 D) $340 E) $360
where Q is the level of output. Letting Z = Q2 and using least-squares estimation, the manager obtains the following computer output:
<strong>refer to the following: A manager wishes to estimate an average cost equation of the following form:   where Q is the level of output. Letting Z = Q<sup>2</sup> and using least-squares estimation, the manager obtains the following computer output:    -When output is 20 units, what is average cost?</strong> A) $160 B) $200 C) $280 D) $340 E) $360

-When output is 20 units, what is average cost?

A) $160
B) $200
C) $280
D) $340
E) $360
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20
A simple linear regression equation relates G and D as follows:
G = a + bD
-The explanatory variable is _______, and the dependent variable is ________.
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21
A simple linear regression equation relates G and D as follows:
G = a + bD
-The slope parameter is ______, and the intercept parameter _______.
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22
A simple linear regression equation relates G and D as follows:
G = a + bD
-When D is zero, G equals _______.
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23
A simple linear regression equation relates G and D as follows:
G = a + bD
-For each one-unit increase in D, the change in R is ______ units.
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24
The linear regression equation G = a + bD is estimated using 24 observations on R and W. The least-squares estimate of b is -22.5, and the standard error of the estimate is 8.36. Perform a t-test for statistical significance of
The linear regression equation G = a + bD is estimated using 24 observations on R and W. The least-squares estimate of b is -22.5, and the standard error of the estimate is 8.36. Perform a t-test for statistical significance of   at the 1% level of significance.  -There are _____ degrees of freedom for the t-test. at the 1% level of significance.

-There are _____ degrees of freedom for the t-test.
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25
The linear regression equation G = a + bD is estimated using 24 observations on R and W. The least-squares estimate of b is -22.5, and the standard error of the estimate is 8.36. Perform a t-test for statistical significance of
The linear regression equation G = a + bD is estimated using 24 observations on R and W. The least-squares estimate of b is -22.5, and the standard error of the estimate is 8.36. Perform a t-test for statistical significance of   at the 1% level of significance.  -The value of the t-statistic is _________. The critical t-value for the test is _________. at the 1% level of significance.

-The value of the t-statistic is _________. The critical t-value for the test is _________.
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26
The linear regression equation G = a + bD is estimated using 24 observations on R and W. The least-squares estimate of b is -22.5, and the standard error of the estimate is 8.36. Perform a t-test for statistical significance of
The linear regression equation G = a + bD is estimated using 24 observations on R and W. The least-squares estimate of b is -22.5, and the standard error of the estimate is 8.36. Perform a t-test for statistical significance of   at the 1% level of significance.  -The parameter estimate _________ (is, is not) statistically significant at the 1% level. at the 1% level of significance.

-The parameter estimate _________ (is, is not) statistically significant at the 1% level.
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27
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is    -The equation of the sample regression line is: = __________________________.

-The equation of the sample regression line is: = __________________________.
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28
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is    -There are ______ degrees of freedom for the t-test. At the 5% level of significance, the critical t-value for the test is ______________.

-There are ______ degrees of freedom for the t-test. At the 5% level of significance, the critical t-value for the test is ______________.
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29
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is    -At the 5% level of significance, __________ (is, not) significant, and ________ (is, is not) significant.

-At the 5% level of significance, __________ (is, not) significant, and ________ (is, is not) significant.
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30
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is    -At the 2% level of significance, the critical t-value for a t-test is ___________. At the 2% level of significance, _________ (is, is not) significant, and _________ (is, is not) significant.

-At the 2% level of significance, the critical t-value for a t-test is ___________. At the 2% level of significance, _________ (is, is not) significant, and _________ (is, is not) significant.
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31
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is    -The p-value for indicates that the exact level of significance is ______ percent, which is the probability of _________________________________________.

-The p-value for indicates that the exact level of significance is ______ percent, which is the probability of _________________________________________.
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32
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is    -At the 5% level of significance, the critical value of the F-statistic is _______. The model as a whole ___________(is, is not) significant at the 5% level.

-At the 5% level of significance, the critical value of the F-statistic is _______. The model as a whole ___________(is, is not) significant at the 5% level.
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33
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is    -If X equals 240, the fitted (or predicted) value of Y is ____________________________.

-If X equals 240, the fitted (or predicted) value of Y is ____________________________.
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34
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is
Thirty-two data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bX. The computer output from the regression analysis is    -The percentage of the total variation in Y that is NOT explained by the regression is ________.

-The percentage of the total variation in Y that is NOT explained by the regression is ________.
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35
4-4F Suppose Y is related to R and S in the following nonlinear way:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -In order to estimate the parameters a, b, and c, the equation must be transformed into the form: ___________________________________.
Twenty-six observations are used to obtain the following regression results:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -In order to estimate the parameters a, b, and c, the equation must be transformed into the form: ___________________________________.
-In order to estimate the parameters a, b, and c, the equation must be transformed into the form: ___________________________________.
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36
4-4F Suppose Y is related to R and S in the following nonlinear way:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -There are _______ degrees of freedom for the t-test. At the 1% level of significance, the critical t-value for the test is __________.
Twenty-six observations are used to obtain the following regression results:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -There are _______ degrees of freedom for the t-test. At the 1% level of significance, the critical t-value for the test is __________.
-There are _______ degrees of freedom for the t-test. At the 1% level of significance, the critical t-value for the test is __________.
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37
4-4F Suppose Y is related to R and S in the following nonlinear way:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -At the 1% level of significance, _______ (is, is not) significant, _______ (is, is not) significant, and ________ (is, is not) significant.
Twenty-six observations are used to obtain the following regression results:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -At the 1% level of significance, _______ (is, is not) significant, _______ (is, is not) significant, and ________ (is, is not) significant.
-At the 1% level of significance, _______ (is, is not) significant, _______ (is, is not) significant, and ________ (is, is not) significant.
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38
4-4F Suppose Y is related to R and S in the following nonlinear way:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -The estimated value of a is ______________.
Twenty-six observations are used to obtain the following regression results:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -The estimated value of a is ______________.
-The estimated value of a is ______________.
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39
4-4F Suppose Y is related to R and S in the following nonlinear way:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -The p-value for indicates that the exact level of significance is _________ percent, which is the probability of _________________.
Twenty-six observations are used to obtain the following regression results:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -The p-value for indicates that the exact level of significance is _________ percent, which is the probability of _________________.
-The p-value for indicates that the exact level of significance is _________ percent, which is the probability of _________________.
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40
4-4F Suppose Y is related to R and S in the following nonlinear way:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -At the 1% level of significance, the critical value of the F-statistic is _________. The model as a whole _________ (is, is not) significant at the 1% level.
Twenty-six observations are used to obtain the following regression results:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -At the 1% level of significance, the critical value of the F-statistic is _________. The model as a whole _________ (is, is not) significant at the 1% level.
-At the 1% level of significance, the critical value of the F-statistic is _________. The model as a whole _________ (is, is not) significant at the 1% level.
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41
4-4F Suppose Y is related to R and S in the following nonlinear way:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -If R equals 12 and S equals 30, the fitted (or predicted) value of Y is _____________.
Twenty-six observations are used to obtain the following regression results:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -If R equals 12 and S equals 30, the fitted (or predicted) value of Y is _____________.
-If R equals 12 and S equals 30, the fitted (or predicted) value of Y is _____________.
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42
4-4F Suppose Y is related to R and S in the following nonlinear way:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -The percentage of the total variation in the dependent variable NOT explained by the regression is _______________.
Twenty-six observations are used to obtain the following regression results:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -The percentage of the total variation in the dependent variable NOT explained by the regression is _______________.
-The percentage of the total variation in the dependent variable NOT explained by the regression is _______________.
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43
4-4F Suppose Y is related to R and S in the following nonlinear way:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -If R increases by 14%, Y will increase by ________ percent.
Twenty-six observations are used to obtain the following regression results:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -If R increases by 14%, Y will increase by ________ percent.
-If R increases by 14%, Y will increase by ________ percent.
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44
4-4F Suppose Y is related to R and S in the following nonlinear way:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -A 6.87% increase in Y will occur if S ________________ (increases, decreases) by _______ percent.
Twenty-six observations are used to obtain the following regression results:
4-4F Suppose Y is related to R and S in the following nonlinear way:   Twenty-six observations are used to obtain the following regression results:   ‪ -A 6.87% increase in Y will occur if S ________________ (increases, decreases) by _______ percent.
-A 6.87% increase in Y will occur if S ________________ (increases, decreases) by _______ percent.
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45
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -The estimated sample regression line is _________________________________. . The computer output from the regression analysis is shown below:
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -The estimated sample regression line is _________________________________.
-The estimated sample regression line is _________________________________.
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46
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -At the 2% level of significance, ‪   _________ (is, is NOT) significant,‪   _________ (is, is NOT) significant,‪   _________ (is, is NOT) significant, and‪   _________ (is, is NOT) significant. . The computer output from the regression analysis is shown below:
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -At the 2% level of significance, ‪   _________ (is, is NOT) significant,‪   _________ (is, is NOT) significant,‪   _________ (is, is NOT) significant, and‪   _________ (is, is NOT) significant.
-At the 2% level of significance, ‪ 4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -At the 2% level of significance, ‪   _________ (is, is NOT) significant,‪   _________ (is, is NOT) significant,‪   _________ (is, is NOT) significant, and‪   _________ (is, is NOT) significant. _________ (is, is NOT) significant,‪ 4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -At the 2% level of significance, ‪   _________ (is, is NOT) significant,‪   _________ (is, is NOT) significant,‪   _________ (is, is NOT) significant, and‪   _________ (is, is NOT) significant. _________ (is, is NOT) significant,‪ 4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -At the 2% level of significance, ‪   _________ (is, is NOT) significant,‪   _________ (is, is NOT) significant,‪   _________ (is, is NOT) significant, and‪   _________ (is, is NOT) significant. _________ (is, is NOT) significant, and‪ 4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -At the 2% level of significance, ‪   _________ (is, is NOT) significant,‪   _________ (is, is NOT) significant,‪   _________ (is, is NOT) significant, and‪   _________ (is, is NOT) significant. _________ (is, is NOT) significant.
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47
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -At the 4% level of significance,   __________ (is, is not) significant,   ________ (is, is not) significant,   ________ (is, is not) significant, and   ________ (is, is not) significant. . The computer output from the regression analysis is shown below:
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -At the 4% level of significance,   __________ (is, is not) significant,   ________ (is, is not) significant,   ________ (is, is not) significant, and   ________ (is, is not) significant.
-At the 4% level of significance, 4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -At the 4% level of significance,   __________ (is, is not) significant,   ________ (is, is not) significant,   ________ (is, is not) significant, and   ________ (is, is not) significant. __________ (is, is not) significant, 4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -At the 4% level of significance,   __________ (is, is not) significant,   ________ (is, is not) significant,   ________ (is, is not) significant, and   ________ (is, is not) significant. ________ (is, is not) significant, 4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -At the 4% level of significance,   __________ (is, is not) significant,   ________ (is, is not) significant,   ________ (is, is not) significant, and   ________ (is, is not) significant. ________ (is, is not) significant, and 4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -At the 4% level of significance,   __________ (is, is not) significant,   ________ (is, is not) significant,   ________ (is, is not) significant, and   ________ (is, is not) significant. ________ (is, is not) significant.
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48
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -The p-value for indicates that the exact level of significance is ______ percent, which is the probability of _______________________________. . The computer output from the regression analysis is shown below:
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -The p-value for indicates that the exact level of significance is ______ percent, which is the probability of _______________________________.
-The p-value for indicates that the exact level of significance is ______ percent, which is the probability of _______________________________.
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49
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -If U equals 4, V equals 8, and W equals 10, the fitted (or predicted) value of H is ____________. . The computer output from the regression analysis is shown below:
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -If U equals 4, V equals 8, and W equals 10, the fitted (or predicted) value of H is ____________.
-If U equals 4, V equals 8, and W equals 10, the fitted (or predicted) value of H is ____________.
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50
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -The percentage of the total variation in H explained by the regression is ________ percent. . The computer output from the regression analysis is shown below:
4-5F Seventy-five data point on H, U, V, and W are employed to estimate the parameters in the linear relation   . The computer output from the regression analysis is shown below:   -The percentage of the total variation in H explained by the regression is ________ percent.
-The percentage of the total variation in H explained by the regression is ________ percent.
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