Deck 12: Simple Linear Regression

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Question
Regression analysis was applied between sales (in $1000) and advertising (in $100) and the following regression function was obtained. <strong>Regression analysis was applied between sales (in $1000) and advertising (in $100) and the following regression function was obtained.   = 500 + 4x Based on the above estimated regression line if advertising is $10,000, then the point estimate for sales (in dollars) is</strong> A)$900 B)$900,000 C)$40,500 D)$505,000 <div style=padding-top: 35px> = 500 + 4x Based on the above estimated regression line if advertising is $10,000, then the point estimate for sales (in dollars) is

A)$900
B)$900,000
C)$40,500
D)$505,000
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Question
Application of the least squares method results in values of the y intercept and the slope that minimizes the sum of the squared deviations between the

A)observed values of the independent variable and the predicted values of the independent variable
B)actual values of the independent variable and predicted values of the dependent variable
C)observed values of the dependent variable and the predicted values of the dependent variable
D)None of these answers is correct.
Question
In a regression analysis, the variable that is being predicted

A)must have the same units as the variable doing the predicting
B)is the independent variable
C)is the dependent variable
D)usually is denoted by x
Question
A measure of the strength of the relationship between two variables is the

A)coefficient of determination
B)slope b1 of the estimated regression line
C)standard error of the estimate
D)correlation coefficient
Question
The least squares criterion is

A)<strong>The least squares criterion is</strong> A)  B)  C)  D)  <div style=padding-top: 35px>
B)<strong>The least squares criterion is</strong> A)  B)  C)  D)  <div style=padding-top: 35px>
C)<strong>The least squares criterion is</strong> A)  B)  C)  D)  <div style=padding-top: 35px>
D)<strong>The least squares criterion is</strong> A)  B)  C)  D)  <div style=padding-top: 35px>
Question
The interval estimate of the mean value of y for a given value of x is the

A)confidence interval
B)prediction interval
C)residual interval
D)correlation interval
Question
The equation that describes how the dependent variable (y) is related to the independent variable (x) is called

A)the correlation model
B)the regression model
C)correlation analysis
D)None of these answers is correct.
Question
Regression analysis was applied between sales (in $1,000) and advertising (in $100), and the following regression function was obtained. <strong>Regression analysis was applied between sales (in $1,000) and advertising (in $100), and the following regression function was obtained.   = 80 + 6.2x Based on the above estimated regression line, if advertising is $10,000, then the point estimate for sales (in dollars) is</strong> A)$62,080 B)$142,000 C)$700 D)$700,000 <div style=padding-top: 35px> = 80 + 6.2x Based on the above estimated regression line, if advertising is $10,000, then the point estimate for sales (in dollars) is

A)$62,080
B)$142,000
C)$700
D)$700,000
Question
A least squares regression line

A)may be used to predict a value of y if the corresponding x value is given
B)implies a cause-effect relationship between x and y
C)can only be determined if a good linear relationship exists between x and y
D)All of these answers are correct.
Question
A procedure used for finding the equation of a straight line that provides the best approximation for the relationship between the independent and dependent variables is the

A)correlation analysis
B)mean squares method
C)least squares method
D)most squares method
Question
In regression analysis if the dependent variable is measured in dollars, the independent variable

A)must also be in dollars
B)must be in some unit of currency
C)can be any units
D)can not be in dollars
Question
The proportion of the variation in the dependent variable y that is explained by the estimated regression equation is measured by the

A)correlation coefficient
B)standard error of the estimate
C)coefficient of determination
D)confidence interval estimate
Question
A regression analysis between demand (y in 1000 units) and price (x in dollars) resulted in the following equation <strong>A regression analysis between demand (y in 1000 units) and price (x in dollars) resulted in the following equation   =9 - 3x The above equation implies that if the price is increased by $1, the demand is expected to</strong> A)increase by 6 units B)decrease by 3 units C)decrease by 6,000 units D)decrease by 3,000 units <div style=padding-top: 35px> =9 - 3x The above equation implies that if the price is increased by $1, the demand is expected to

A)increase by 6 units
B)decrease by 3 units
C)decrease by 6,000 units
D)decrease by 3,000 units
Question
In a simple regression analysis (where y is a dependent and x an independent variable), if the y intercept is positive, then

A)there is a positive correlation between x and y
B)there is a negative correlation between x and y
C)if x is increased, y must also increase
D)None of these answers is correct.
Question
In a residual plot against x that does not suggest we should challenge the assumptions of our regression model, we would expect to see

A)a horizontal band of points centered near zero
B)a widening band of points
C)a band of points having a slope consistent with that of the regression equation
D)a parabolic band of points
Question
In regression analysis, the independent variable is

A)used to predict other independent variables
B)used to predict the dependent variable
C)called the intervening variable
D)None of these answers is correct.
Question
In regression analysis, the variable that is being predicted is the

A)dependent variable
B)independent variable
C)intervening variable
D)None of these answers is correct.
Question
The difference between the observed value of the dependent variable and the value predicted by using the estimated regression equation is the

A)standard error
B)residual
C)prediction interval
D)variance
Question
Regression analysis is a statistical procedure for developing a mathematical equation that describes how

A)one independent and one or more dependent variables are related
B)several independent and several dependent variables are related
C)one dependent and one or more independent variables are related
D)None of these answers is correct.
Question
As the goodness of fit for the estimated regression equation increases,

A)the absolute value of the regression equation's slope increases
B)the value of the regression equation's y intercept decreases
C)the value of the coefficient of determination increases
D)the value of the correlation coefficient increases
Question
SSE can never be

A)larger than SST
B)smaller than SST
C)equal to 1
D)equal to zero
Question
If there is a very strong correlation between two variables, then the coefficient of correlation must be

A)much larger than 1, if the correlation is positive
B)much smaller than 1, if the correlation is negative
C)either much larger than 1 or much smaller than 1
D)None of these answers is correct.
Question
If the coefficient of correlation is 0.8, the percentage of variation in the dependent variable explained by the estimated regression equation is

A)0.80%
B)80%
C)0.64%
D)64%
Question
In regression and correlation analysis, if SSE and SST are known, then with this information the

A)coefficient of determination can be computed
B)slope of the line can be computed
C)y intercept can be computed
D)All of the above can be computed.
Question
In a regression analysis if r2 = 1, then

A)SSE must also be equal to one
B)SSE must be equal to zero
C)SSE can be any positive value
D)SSE must be negative
Question
In a regression analysis if SSE = 500 and SSR =300, then the coefficient of determination is

A)0.6000
B)0.1666
C)1.6666
D)0.3750
Question
If the coefficient of determination is a positive value, then the regression equation

A)must have a positive slope
B)must have a negative slope
C)could have either a positive or a negative slope
D)must have a positive y intercept
Question
In simple linear regression, r2 is the

A)estimated regression equation
B)coefficient of correlation
C)sum of the squared residuals
D)coefficient of determination
Question
If all the points of a scatter diagram lie on the least squares regression line, then the coefficient of determination for these variables based on this data is

A)0
B)1
C)either 1 or -1, depending upon whether the relationship is positive or negative
D)could be any value between -1 and 1
Question
If the coefficient of determination is equal to 1, then the coefficient of correlation

A)must also be equal to 1
B)can be either -1 or +1
C)can be any value between -1 to +1
D)must be -1
Question
Which of the following is correct?

A)SSE = SSR +SST
B)SSR = SSE +SST
C)SST =SSR + SSE
D)SST= (SSR)2
Question
In a regression analysis if SSE=200 and SSR =300, then the coefficient of determination is

A)0.6667
B)0.6000
C)0.4000
D)1.5000
Question
In a regression analysis if r2 = 1, then

A)SSE = SST
B)SSE = 1
C)SSR = SSE
D)SSR = SST
Question
Larger values of r2 imply that the observations are more closely grouped about the

A)average value of the independent variables
B)average value of the dependent variable
C)least squares line
D)origin
Question
It is possible for the coefficient of determination to be

A)larger than 1
B)less than one
C)less than zero
D)All of these answers are correct, depending on the situation under consideration.
Question
A regression analysis between sales (y in $1000) and advertising (x in dollars) resulted in the following equation <strong>A regression analysis between sales (y in $1000) and advertising (x in dollars) resulted in the following equation   = 50,000 + 6x The above equation implies that an</strong> A)increase of $6 in advertising is associated with an increase of $6,000 in sales B)increase of $1 in advertising is associated with an increase of $6 in sales C)increase of $1 in advertising is associated with an increase of $56,000 in sales D)increase of $1 in advertising is associated with an increase of $6,000 in sales <div style=padding-top: 35px> = 50,000 + 6x The above equation implies that an

A)increase of $6 in advertising is associated with an increase of $6,000 in sales
B)increase of $1 in advertising is associated with an increase of $6 in sales
C)increase of $1 in advertising is associated with an increase of $56,000 in sales
D)increase of $1 in advertising is associated with an increase of $6,000 in sales
Question
If a data set has SST = 2,000 and SSE =800, then the coefficient of determination is

A)0.4
B)0.6
C)0.5
D)0.8
Question
In a regression analysis if SST = 4500 and SSE=1575, then the coefficient of determination is

A)0.35
B)0.65
C)2.85
D)0.45
Question
If the coefficient of correlation is 0.4, the percentage of variation in the dependent variable explained by the estimated regression equation

A)is 40%
B)is 16%
C)is 4%
D)can be any positive value
Question
A regression analysis between sales (in $1000) and price (in dollars) resulted in the following equation <strong>A regression analysis between sales (in $1000) and price (in dollars) resulted in the following equation   =50,000 - 8x The above equation implies that an</strong> A)increase of $1 in price is associated with a decrease of $8 in sales B)increase of $8 in price is associated with an increase of $8,000 in sales C)increase of $1 in price is associated with a decrease of $42,000 in sales D)increase of $1 in price is associated with a decrease of $8000 in sales <div style=padding-top: 35px> =50,000 - 8x The above equation implies that an

A)increase of $1 in price is associated with a decrease of $8 in sales
B)increase of $8 in price is associated with an increase of $8,000 in sales
C)increase of $1 in price is associated with a decrease of $42,000 in sales
D)increase of $1 in price is associated with a decrease of $8000 in sales
Question
In simple linear regression analysis, which of the following is not true?

A)The F test and the t test yield the same results.
B)The F test and the t test may or may not yield the same results.
C)The relationship between x and y is represented by means of a straight line.
D)The value of F = t2.
Question
Exhibit 12-1
A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x).
<strong>Exhibit 12-1 A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x).    -Refer to Exhibit 12-1. The point estimate of y when x = 20 is</strong> A)0 B)31 C)9 D)-9 <div style=padding-top: 35px>

-Refer to Exhibit 12-1. The point estimate of y when x = 20 is

A)0
B)31
C)9
D)-9
Question
If the coefficient of correlation is a negative value, then the coefficient of determination

A)must also be negative
B)must be zero
C)can be either negative or positive
D)must be positive
Question
If the coefficient of determination is 0.81, the coefficient of correlation

A)is 0.6561
B)must be 0.9
C)must be positive
D)None of these answers is correct.
Question
Data points having high leverage are often

A)residuals
B)sum of squares error
C)influential
D)None of the other answers is correct.
Question
Exhibit 12-2
You are given the following information about y and x.
<strong>Exhibit 12-2 You are given the following information about y and x.   Refer to Exhibit 12-2. The least squares estimate of b<sub>0</sub> equals</strong> A)-7.647 B)-1.3 C)21.4 D)16.41176 <div style=padding-top: 35px>
Refer to Exhibit 12-2. The least squares estimate of b0 equals

A)-7.647
B)-1.3
C)21.4
D)16.41176
Question
If the coefficient of correlation is a positive value, then the slope of the regression line

A)must also be positive
B)can be either negative or positive
C)can be zero
D)None of these answers is correct.
Question
The numerical value of the coefficient of determination

A)is always larger than the coefficient of correlation
B)is always smaller than the coefficient of correlation
C)is negative if the coefficient of determination is negative
D)can be larger or smaller than the coefficient of correlation
Question
In regression analysis, which of the following is not a required assumption about the error term ε\varepsilon ?

A)The expected value of the error term is zero.
B)The variance of the error term is the same for all values of x.
C)The values of the error term are independent.
D)All are required assumptions about the error term.
Question
A data point (observation) that does not fit the trend shown by the remaining data is called a(n)

A)residual
B)outlier
C)point estimate
D)None of the other answers is correct.
Question
Exhibit 12-1
A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x).
<strong>Exhibit 12-1 A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x).   Refer to Exhibit 12-1. The least squares estimate of b<sub>0</sub> equals</strong> A)1 B)-1 C)5.5 D)11 <div style=padding-top: 35px>
Refer to Exhibit 12-1. The least squares estimate of b0 equals

A)1
B)-1
C)5.5
D)11
Question
If two variables, x and y, have a strong linear relationship, then

A)there may or may not be any causal relationship between x and y
B)x causes y to happen
C)y causes x to happen
D)None of these answers is correct.
Question
Exhibit 12-1
A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x).
<strong>Exhibit 12-1 A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x).   Refer to Exhibit 12-1. The coefficient of determination equals</strong> A)0 B)-1 C)+1 D)-0.5 <div style=padding-top: 35px>
Refer to Exhibit 12-1. The coefficient of determination equals

A)0
B)-1
C)+1
D)-0.5
Question
Compared to the confidence interval estimate for a particular value of y (in a linear regression model), the interval estimate for an average value of y will be

A)narrower
B)wider
C)the same
D)Not enough information is given.
Question
Exhibit 12-1
A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x).
<strong>Exhibit 12-1 A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x).   Refer to Exhibit 12-1. The sample correlation coefficient equals</strong> A)0 B)-1 C)+1 D)-0.5 <div style=padding-top: 35px>
Refer to Exhibit 12-1. The sample correlation coefficient equals

A)0
B)-1
C)+1
D)-0.5
Question
An observation that has a strong effect on the regression results is called a(n)

A)residual
B)sum of squares error
C)influential observation
D)None of the other answers is correct.
Question
Exhibit 12-1
A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x).
<strong>Exhibit 12-1 A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x).   Refer to Exhibit 12-1. The least squares estimate of b<sub>1</sub> equals</strong> A)1 B)-1 C)5.5 D)11 <div style=padding-top: 35px>
Refer to Exhibit 12-1. The least squares estimate of b1 equals

A)1
B)-1
C)5.5
D)11
Question
Exhibit 12-2
You are given the following information about y and x.
<strong>Exhibit 12-2 You are given the following information about y and x.   Refer to Exhibit 12-2. The coefficient of determination equals</strong> A)-0.99705 B)-0.9941 C)0.9941 D)0.99705 <div style=padding-top: 35px>
Refer to Exhibit 12-2. The coefficient of determination equals

A)-0.99705
B)-0.9941
C)0.9941
D)0.99705
Question
Exhibit 12-2
You are given the following information about y and x.
<strong>Exhibit 12-2 You are given the following information about y and x.   Refer to Exhibit 12-2. The least squares estimate of b<sub>1</sub> equals</strong> A)-0.7647 B)-0.13 C)21.4 D)16.412 <div style=padding-top: 35px>
Refer to Exhibit 12-2. The least squares estimate of b1 equals

A)-0.7647
B)-0.13
C)21.4
D)16.412
Question
Exhibit 12-2
You are given the following information about y and x.
<strong>Exhibit 12-2 You are given the following information about y and x.   Refer to Exhibit 12-2. The sample correlation coefficient equals</strong> A)-86.667 B)-0.99705 C)0.9941 D)0.99705 <div style=padding-top: 35px>
Refer to Exhibit 12-2. The sample correlation coefficient equals

A)-86.667
B)-0.99705
C)0.9941
D)0.99705
Question
Exhibit 12-4
The following information regarding a dependent variable (Y) and an independent variable (X) is provided.
<strong>Exhibit 12-4 The following information regarding a dependent variable (Y) and an independent variable (X) is provided.   SSE = 6 SST = 16 Refer to Exhibit 12-4. The coefficient of correlation is</strong> A)0.7906 B)- 0.7906 C)0.625 D)0.375 <div style=padding-top: 35px> SSE = 6
SST = 16
Refer to Exhibit 12-4. The coefficient of correlation is

A)0.7906
B)- 0.7906
C)0.625
D)0.375
Question
Exhibit 12-6
You are given the following information about y and x.
<strong>Exhibit 12-6 You are given the following information about y and x.   Refer to Exhibit 12-6. The least squares estimate of b<sub>0</sub> equals</strong> A)1 B)-1 C)-11 D)11 <div style=padding-top: 35px>
Refer to Exhibit 12-6. The least squares estimate of b0 equals

A)1
B)-1
C)-11
D)11
Question
Exhibit 12-6
You are given the following information about y and x.
<strong>Exhibit 12-6 You are given the following information about y and x.   Refer to Exhibit 12-6. The coefficient of determination equals</strong> A)-0.4364 B)0.4364 C)-0.1905 D)0.1905 <div style=padding-top: 35px>
Refer to Exhibit 12-6. The coefficient of determination equals

A)-0.4364
B)0.4364
C)-0.1905
D)0.1905
Question
Exhibit 12-5
You are given the following information about y and x.
<strong>Exhibit 12-5 You are given the following information about y and x.   Refer to Exhibit 12-5. The point estimate of y when x = 10 is</strong> A)-10 B)10 C)-4 D)4 <div style=padding-top: 35px>
Refer to Exhibit 12-5. The point estimate of y when x = 10 is

A)-10
B)10
C)-4
D)4
Question
Exhibit 12-3
Regression analysis was applied between sales data (in $1,000s) and advertising data (in $100s) and the following information was obtained.
<strong>Exhibit 12-3 Regression analysis was applied between sales data (in $1,000s) and advertising data (in $100s) and the following information was obtained.   Refer to Exhibit 12-3. Based on the above estimated regression equation, if advertising is $3,000, then the point estimate for sales (in dollars) is</strong> A)$66,000 B)$5,412 C)$66 D)$17,400 <div style=padding-top: 35px>
Refer to Exhibit 12-3. Based on the above estimated regression equation, if advertising is $3,000, then the point estimate for sales (in dollars) is

A)$66,000
B)$5,412
C)$66
D)$17,400
Question
Exhibit 12-4
The following information regarding a dependent variable (Y) and an independent variable (X) is provided.
<strong>Exhibit 12-4 The following information regarding a dependent variable (Y) and an independent variable (X) is provided.   SSE = 6 SST = 16 Refer to Exhibit 12-4. The coefficient of determination is</strong> A)0.7096 B)- 0.7906 C)0.625 D)0.375 <div style=padding-top: 35px> SSE = 6
SST = 16
Refer to Exhibit 12-4. The coefficient of determination is

A)0.7096
B)- 0.7906
C)0.625
D)0.375
Question
Exhibit 12-6
You are given the following information about y and x.
<strong>Exhibit 12-6 You are given the following information about y and x.   Refer to Exhibit 12-6. The sample correlation coefficient equals</strong> A)-0.4364 B)0.4364 C)-0.1905 D)0.1905 <div style=padding-top: 35px>
Refer to Exhibit 12-6. The sample correlation coefficient equals

A)-0.4364
B)0.4364
C)-0.1905
D)0.1905
Question
Exhibit 12-5
You are given the following information about y and x.
<strong>Exhibit 12-5 You are given the following information about y and x.   Refer to Exhibit 12-5. The sample correlation coefficient equals</strong> A)0 B)+1 C)-1 D)-0.5 <div style=padding-top: 35px>
Refer to Exhibit 12-5. The sample correlation coefficient equals

A)0
B)+1
C)-1
D)-0.5
Question
Exhibit 12-6
You are given the following information about y and x.
<strong>Exhibit 12-6 You are given the following information about y and x.   Refer to Exhibit 12-6. The least squares estimate of b<sub>1</sub> equals</strong> A)1 B)-1 C)-11 D)11 <div style=padding-top: 35px>
Refer to Exhibit 12-6. The least squares estimate of b1 equals

A)1
B)-1
C)-11
D)11
Question
Exhibit 12-3
Regression analysis was applied between sales data (in $1,000s) and advertising data (in $100s) and the following information was obtained.
<strong>Exhibit 12-3 Regression analysis was applied between sales data (in $1,000s) and advertising data (in $100s) and the following information was obtained.   Refer to Exhibit 12-3. The t statistic for testing the significance of the slope is</strong> A)1.80 B)1.96 C)6.709 D)0.555 <div style=padding-top: 35px>
Refer to Exhibit 12-3. The t statistic for testing the significance of the slope is

A)1.80
B)1.96
C)6.709
D)0.555
Question
Exhibit 12-5
You are given the following information about y and x.
<strong>Exhibit 12-5 You are given the following information about y and x.   Refer to Exhibit 12-5. The coefficient of determination equals</strong> A)0 B)-1 C)+1 D)-0.5 <div style=padding-top: 35px>
Refer to Exhibit 12-5. The coefficient of determination equals

A)0
B)-1
C)+1
D)-0.5
Question
Given below are seven observations collected in a regression study on two variables, x (independent variable) and y (dependent variable).
Given below are seven observations collected in a regression study on two variables, x (independent variable) and y (dependent variable).   a.Develop the least squares estimated regression equation. b.At 95% confidence, perform a t test and determine whether or not the slope is significantly different from zero. c.Perform an F test to determine whether or not the model is significant. Let <font face=symbol></font> <font face=symbol></font> 0.05. d.Compute the coefficient of determination.<div style=padding-top: 35px>
a.Develop the least squares estimated regression equation.
b.At 95% confidence, perform a t test and determine whether or not the slope is significantly different from zero.
c.Perform an F test to determine whether or not the model is significant. Let 0.05.
d.Compute the coefficient of determination.
Question
Exhibit 12-4
The following information regarding a dependent variable (Y) and an independent variable (X) is provided.
<strong>Exhibit 12-4 The following information regarding a dependent variable (Y) and an independent variable (X) is provided.   SSE = 6 SST = 16 Refer to Exhibit 12-4. The least squares estimate of the slope is</strong> A)1 B)2 C)3 D)4 <div style=padding-top: 35px> SSE = 6
SST = 16
Refer to Exhibit 12-4. The least squares estimate of the slope is

A)1
B)2
C)3
D)4
Question
Exhibit 12-3
Regression analysis was applied between sales data (in $1,000s) and advertising data (in $100s) and the following information was obtained.
<strong>Exhibit 12-3 Regression analysis was applied between sales data (in $1,000s) and advertising data (in $100s) and the following information was obtained.   Refer to Exhibit 12-3. The F statistic computed from the above data is</strong> A)3 B)45 C)48 D)Not enough information is given to answer this question. <div style=padding-top: 35px>
Refer to Exhibit 12-3. The F statistic computed from the above data is

A)3
B)45
C)48
D)Not enough information is given to answer this question.
Question
Exhibit 12-5
You are given the following information about y and x.
<strong>Exhibit 12-5 You are given the following information about y and x.   Refer to Exhibit 12-5. The least squares estimate of b<sub>0</sub> (intercept)equals</strong> A)1 B)-1 C)6 D)5 <div style=padding-top: 35px>
Refer to Exhibit 12-5. The least squares estimate of b0 (intercept)equals

A)1
B)-1
C)6
D)5
Question
Exhibit 12-4
The following information regarding a dependent variable (Y) and an independent variable (X) is provided.
<strong>Exhibit 12-4 The following information regarding a dependent variable (Y) and an independent variable (X) is provided.   SSE = 6 SST = 16 Refer to Exhibit 12-4. The MSE is</strong> A)1 B)2 C)3 D)4 <div style=padding-top: 35px> SSE = 6
SST = 16
Refer to Exhibit 12-4. The MSE is

A)1
B)2
C)3
D)4
Question
Exhibit 12-3
Regression analysis was applied between sales data (in $1,000s) and advertising data (in $100s) and the following information was obtained.
 <strong>Exhibit 12-3 Regression analysis was applied between sales data (in $1,000s) and advertising data (in $100s) and the following information was obtained.    -Refer to Exhibit 12-3. The critical F value at  \alpha =0.05 is</strong> A)3.59 B)3.68 C)4.45 D)4.54 <div style=padding-top: 35px>

-Refer to Exhibit 12-3. The critical F value at α\alpha =0.05 is

A)3.59
B)3.68
C)4.45
D)4.54
Question
Exhibit 12-3
Regression analysis was applied between sales data (in $1,000s) and advertising data (in $100s) and the following information was obtained.
 <strong>Exhibit 12-3 Regression analysis was applied between sales data (in $1,000s) and advertising data (in $100s) and the following information was obtained.    -Refer to Exhibit 12-3. Using  \alpha  =0.05, the critical t value for testing the significance of the slope is</strong> A)1.753 B)2.131 C)1.746 D)2.120 <div style=padding-top: 35px>

-Refer to Exhibit 12-3. Using α\alpha =0.05, the critical t value for testing the significance of the slope is

A)1.753
B)2.131
C)1.746
D)2.120
Question
Exhibit 12-4
The following information regarding a dependent variable (Y) and an independent variable (X) is provided.
<strong>Exhibit 12-4 The following information regarding a dependent variable (Y) and an independent variable (X) is provided.   SSE = 6 SST = 16 Refer to Exhibit 12-4. The least squares estimate of the Y intercept is</strong> A)1 B)2 C)3 D)4 <div style=padding-top: 35px> SSE = 6
SST = 16
Refer to Exhibit 12-4. The least squares estimate of the Y intercept is

A)1
B)2
C)3
D)4
Question
Exhibit 12-5
You are given the following information about y and x.
<strong>Exhibit 12-5 You are given the following information about y and x.   Refer to Exhibit 12-5. The least squares estimate of b<sub>1</sub> (slope) equals</strong> A)1 B)-1 C)6 D)5 <div style=padding-top: 35px>
Refer to Exhibit 12-5. The least squares estimate of b1 (slope) equals

A)1
B)-1
C)6
D)5
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Deck 12: Simple Linear Regression
1
Regression analysis was applied between sales (in $1000) and advertising (in $100) and the following regression function was obtained. <strong>Regression analysis was applied between sales (in $1000) and advertising (in $100) and the following regression function was obtained.   = 500 + 4x Based on the above estimated regression line if advertising is $10,000, then the point estimate for sales (in dollars) is</strong> A)$900 B)$900,000 C)$40,500 D)$505,000 = 500 + 4x Based on the above estimated regression line if advertising is $10,000, then the point estimate for sales (in dollars) is

A)$900
B)$900,000
C)$40,500
D)$505,000
$900,000
2
Application of the least squares method results in values of the y intercept and the slope that minimizes the sum of the squared deviations between the

A)observed values of the independent variable and the predicted values of the independent variable
B)actual values of the independent variable and predicted values of the dependent variable
C)observed values of the dependent variable and the predicted values of the dependent variable
D)None of these answers is correct.
observed values of the dependent variable and the predicted values of the dependent variable
3
In a regression analysis, the variable that is being predicted

A)must have the same units as the variable doing the predicting
B)is the independent variable
C)is the dependent variable
D)usually is denoted by x
is the dependent variable
4
A measure of the strength of the relationship between two variables is the

A)coefficient of determination
B)slope b1 of the estimated regression line
C)standard error of the estimate
D)correlation coefficient
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5
The least squares criterion is

A)<strong>The least squares criterion is</strong> A)  B)  C)  D)
B)<strong>The least squares criterion is</strong> A)  B)  C)  D)
C)<strong>The least squares criterion is</strong> A)  B)  C)  D)
D)<strong>The least squares criterion is</strong> A)  B)  C)  D)
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6
The interval estimate of the mean value of y for a given value of x is the

A)confidence interval
B)prediction interval
C)residual interval
D)correlation interval
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7
The equation that describes how the dependent variable (y) is related to the independent variable (x) is called

A)the correlation model
B)the regression model
C)correlation analysis
D)None of these answers is correct.
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8
Regression analysis was applied between sales (in $1,000) and advertising (in $100), and the following regression function was obtained. <strong>Regression analysis was applied between sales (in $1,000) and advertising (in $100), and the following regression function was obtained.   = 80 + 6.2x Based on the above estimated regression line, if advertising is $10,000, then the point estimate for sales (in dollars) is</strong> A)$62,080 B)$142,000 C)$700 D)$700,000 = 80 + 6.2x Based on the above estimated regression line, if advertising is $10,000, then the point estimate for sales (in dollars) is

A)$62,080
B)$142,000
C)$700
D)$700,000
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9
A least squares regression line

A)may be used to predict a value of y if the corresponding x value is given
B)implies a cause-effect relationship between x and y
C)can only be determined if a good linear relationship exists between x and y
D)All of these answers are correct.
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10
A procedure used for finding the equation of a straight line that provides the best approximation for the relationship between the independent and dependent variables is the

A)correlation analysis
B)mean squares method
C)least squares method
D)most squares method
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11
In regression analysis if the dependent variable is measured in dollars, the independent variable

A)must also be in dollars
B)must be in some unit of currency
C)can be any units
D)can not be in dollars
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12
The proportion of the variation in the dependent variable y that is explained by the estimated regression equation is measured by the

A)correlation coefficient
B)standard error of the estimate
C)coefficient of determination
D)confidence interval estimate
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13
A regression analysis between demand (y in 1000 units) and price (x in dollars) resulted in the following equation <strong>A regression analysis between demand (y in 1000 units) and price (x in dollars) resulted in the following equation   =9 - 3x The above equation implies that if the price is increased by $1, the demand is expected to</strong> A)increase by 6 units B)decrease by 3 units C)decrease by 6,000 units D)decrease by 3,000 units =9 - 3x The above equation implies that if the price is increased by $1, the demand is expected to

A)increase by 6 units
B)decrease by 3 units
C)decrease by 6,000 units
D)decrease by 3,000 units
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14
In a simple regression analysis (where y is a dependent and x an independent variable), if the y intercept is positive, then

A)there is a positive correlation between x and y
B)there is a negative correlation between x and y
C)if x is increased, y must also increase
D)None of these answers is correct.
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15
In a residual plot against x that does not suggest we should challenge the assumptions of our regression model, we would expect to see

A)a horizontal band of points centered near zero
B)a widening band of points
C)a band of points having a slope consistent with that of the regression equation
D)a parabolic band of points
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16
In regression analysis, the independent variable is

A)used to predict other independent variables
B)used to predict the dependent variable
C)called the intervening variable
D)None of these answers is correct.
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17
In regression analysis, the variable that is being predicted is the

A)dependent variable
B)independent variable
C)intervening variable
D)None of these answers is correct.
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18
The difference between the observed value of the dependent variable and the value predicted by using the estimated regression equation is the

A)standard error
B)residual
C)prediction interval
D)variance
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19
Regression analysis is a statistical procedure for developing a mathematical equation that describes how

A)one independent and one or more dependent variables are related
B)several independent and several dependent variables are related
C)one dependent and one or more independent variables are related
D)None of these answers is correct.
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20
As the goodness of fit for the estimated regression equation increases,

A)the absolute value of the regression equation's slope increases
B)the value of the regression equation's y intercept decreases
C)the value of the coefficient of determination increases
D)the value of the correlation coefficient increases
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21
SSE can never be

A)larger than SST
B)smaller than SST
C)equal to 1
D)equal to zero
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22
If there is a very strong correlation between two variables, then the coefficient of correlation must be

A)much larger than 1, if the correlation is positive
B)much smaller than 1, if the correlation is negative
C)either much larger than 1 or much smaller than 1
D)None of these answers is correct.
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23
If the coefficient of correlation is 0.8, the percentage of variation in the dependent variable explained by the estimated regression equation is

A)0.80%
B)80%
C)0.64%
D)64%
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24
In regression and correlation analysis, if SSE and SST are known, then with this information the

A)coefficient of determination can be computed
B)slope of the line can be computed
C)y intercept can be computed
D)All of the above can be computed.
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25
In a regression analysis if r2 = 1, then

A)SSE must also be equal to one
B)SSE must be equal to zero
C)SSE can be any positive value
D)SSE must be negative
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26
In a regression analysis if SSE = 500 and SSR =300, then the coefficient of determination is

A)0.6000
B)0.1666
C)1.6666
D)0.3750
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27
If the coefficient of determination is a positive value, then the regression equation

A)must have a positive slope
B)must have a negative slope
C)could have either a positive or a negative slope
D)must have a positive y intercept
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28
In simple linear regression, r2 is the

A)estimated regression equation
B)coefficient of correlation
C)sum of the squared residuals
D)coefficient of determination
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29
If all the points of a scatter diagram lie on the least squares regression line, then the coefficient of determination for these variables based on this data is

A)0
B)1
C)either 1 or -1, depending upon whether the relationship is positive or negative
D)could be any value between -1 and 1
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30
If the coefficient of determination is equal to 1, then the coefficient of correlation

A)must also be equal to 1
B)can be either -1 or +1
C)can be any value between -1 to +1
D)must be -1
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31
Which of the following is correct?

A)SSE = SSR +SST
B)SSR = SSE +SST
C)SST =SSR + SSE
D)SST= (SSR)2
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32
In a regression analysis if SSE=200 and SSR =300, then the coefficient of determination is

A)0.6667
B)0.6000
C)0.4000
D)1.5000
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33
In a regression analysis if r2 = 1, then

A)SSE = SST
B)SSE = 1
C)SSR = SSE
D)SSR = SST
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34
Larger values of r2 imply that the observations are more closely grouped about the

A)average value of the independent variables
B)average value of the dependent variable
C)least squares line
D)origin
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35
It is possible for the coefficient of determination to be

A)larger than 1
B)less than one
C)less than zero
D)All of these answers are correct, depending on the situation under consideration.
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36
A regression analysis between sales (y in $1000) and advertising (x in dollars) resulted in the following equation <strong>A regression analysis between sales (y in $1000) and advertising (x in dollars) resulted in the following equation   = 50,000 + 6x The above equation implies that an</strong> A)increase of $6 in advertising is associated with an increase of $6,000 in sales B)increase of $1 in advertising is associated with an increase of $6 in sales C)increase of $1 in advertising is associated with an increase of $56,000 in sales D)increase of $1 in advertising is associated with an increase of $6,000 in sales = 50,000 + 6x The above equation implies that an

A)increase of $6 in advertising is associated with an increase of $6,000 in sales
B)increase of $1 in advertising is associated with an increase of $6 in sales
C)increase of $1 in advertising is associated with an increase of $56,000 in sales
D)increase of $1 in advertising is associated with an increase of $6,000 in sales
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37
If a data set has SST = 2,000 and SSE =800, then the coefficient of determination is

A)0.4
B)0.6
C)0.5
D)0.8
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38
In a regression analysis if SST = 4500 and SSE=1575, then the coefficient of determination is

A)0.35
B)0.65
C)2.85
D)0.45
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39
If the coefficient of correlation is 0.4, the percentage of variation in the dependent variable explained by the estimated regression equation

A)is 40%
B)is 16%
C)is 4%
D)can be any positive value
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40
A regression analysis between sales (in $1000) and price (in dollars) resulted in the following equation <strong>A regression analysis between sales (in $1000) and price (in dollars) resulted in the following equation   =50,000 - 8x The above equation implies that an</strong> A)increase of $1 in price is associated with a decrease of $8 in sales B)increase of $8 in price is associated with an increase of $8,000 in sales C)increase of $1 in price is associated with a decrease of $42,000 in sales D)increase of $1 in price is associated with a decrease of $8000 in sales =50,000 - 8x The above equation implies that an

A)increase of $1 in price is associated with a decrease of $8 in sales
B)increase of $8 in price is associated with an increase of $8,000 in sales
C)increase of $1 in price is associated with a decrease of $42,000 in sales
D)increase of $1 in price is associated with a decrease of $8000 in sales
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41
In simple linear regression analysis, which of the following is not true?

A)The F test and the t test yield the same results.
B)The F test and the t test may or may not yield the same results.
C)The relationship between x and y is represented by means of a straight line.
D)The value of F = t2.
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42
Exhibit 12-1
A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x).
<strong>Exhibit 12-1 A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x).    -Refer to Exhibit 12-1. The point estimate of y when x = 20 is</strong> A)0 B)31 C)9 D)-9

-Refer to Exhibit 12-1. The point estimate of y when x = 20 is

A)0
B)31
C)9
D)-9
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43
If the coefficient of correlation is a negative value, then the coefficient of determination

A)must also be negative
B)must be zero
C)can be either negative or positive
D)must be positive
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44
If the coefficient of determination is 0.81, the coefficient of correlation

A)is 0.6561
B)must be 0.9
C)must be positive
D)None of these answers is correct.
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45
Data points having high leverage are often

A)residuals
B)sum of squares error
C)influential
D)None of the other answers is correct.
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46
Exhibit 12-2
You are given the following information about y and x.
<strong>Exhibit 12-2 You are given the following information about y and x.   Refer to Exhibit 12-2. The least squares estimate of b<sub>0</sub> equals</strong> A)-7.647 B)-1.3 C)21.4 D)16.41176
Refer to Exhibit 12-2. The least squares estimate of b0 equals

A)-7.647
B)-1.3
C)21.4
D)16.41176
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47
If the coefficient of correlation is a positive value, then the slope of the regression line

A)must also be positive
B)can be either negative or positive
C)can be zero
D)None of these answers is correct.
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48
The numerical value of the coefficient of determination

A)is always larger than the coefficient of correlation
B)is always smaller than the coefficient of correlation
C)is negative if the coefficient of determination is negative
D)can be larger or smaller than the coefficient of correlation
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49
In regression analysis, which of the following is not a required assumption about the error term ε\varepsilon ?

A)The expected value of the error term is zero.
B)The variance of the error term is the same for all values of x.
C)The values of the error term are independent.
D)All are required assumptions about the error term.
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50
A data point (observation) that does not fit the trend shown by the remaining data is called a(n)

A)residual
B)outlier
C)point estimate
D)None of the other answers is correct.
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51
Exhibit 12-1
A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x).
<strong>Exhibit 12-1 A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x).   Refer to Exhibit 12-1. The least squares estimate of b<sub>0</sub> equals</strong> A)1 B)-1 C)5.5 D)11
Refer to Exhibit 12-1. The least squares estimate of b0 equals

A)1
B)-1
C)5.5
D)11
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52
If two variables, x and y, have a strong linear relationship, then

A)there may or may not be any causal relationship between x and y
B)x causes y to happen
C)y causes x to happen
D)None of these answers is correct.
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53
Exhibit 12-1
A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x).
<strong>Exhibit 12-1 A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x).   Refer to Exhibit 12-1. The coefficient of determination equals</strong> A)0 B)-1 C)+1 D)-0.5
Refer to Exhibit 12-1. The coefficient of determination equals

A)0
B)-1
C)+1
D)-0.5
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54
Compared to the confidence interval estimate for a particular value of y (in a linear regression model), the interval estimate for an average value of y will be

A)narrower
B)wider
C)the same
D)Not enough information is given.
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55
Exhibit 12-1
A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x).
<strong>Exhibit 12-1 A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x).   Refer to Exhibit 12-1. The sample correlation coefficient equals</strong> A)0 B)-1 C)+1 D)-0.5
Refer to Exhibit 12-1. The sample correlation coefficient equals

A)0
B)-1
C)+1
D)-0.5
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56
An observation that has a strong effect on the regression results is called a(n)

A)residual
B)sum of squares error
C)influential observation
D)None of the other answers is correct.
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57
Exhibit 12-1
A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x).
<strong>Exhibit 12-1 A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x).   Refer to Exhibit 12-1. The least squares estimate of b<sub>1</sub> equals</strong> A)1 B)-1 C)5.5 D)11
Refer to Exhibit 12-1. The least squares estimate of b1 equals

A)1
B)-1
C)5.5
D)11
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58
Exhibit 12-2
You are given the following information about y and x.
<strong>Exhibit 12-2 You are given the following information about y and x.   Refer to Exhibit 12-2. The coefficient of determination equals</strong> A)-0.99705 B)-0.9941 C)0.9941 D)0.99705
Refer to Exhibit 12-2. The coefficient of determination equals

A)-0.99705
B)-0.9941
C)0.9941
D)0.99705
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59
Exhibit 12-2
You are given the following information about y and x.
<strong>Exhibit 12-2 You are given the following information about y and x.   Refer to Exhibit 12-2. The least squares estimate of b<sub>1</sub> equals</strong> A)-0.7647 B)-0.13 C)21.4 D)16.412
Refer to Exhibit 12-2. The least squares estimate of b1 equals

A)-0.7647
B)-0.13
C)21.4
D)16.412
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60
Exhibit 12-2
You are given the following information about y and x.
<strong>Exhibit 12-2 You are given the following information about y and x.   Refer to Exhibit 12-2. The sample correlation coefficient equals</strong> A)-86.667 B)-0.99705 C)0.9941 D)0.99705
Refer to Exhibit 12-2. The sample correlation coefficient equals

A)-86.667
B)-0.99705
C)0.9941
D)0.99705
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61
Exhibit 12-4
The following information regarding a dependent variable (Y) and an independent variable (X) is provided.
<strong>Exhibit 12-4 The following information regarding a dependent variable (Y) and an independent variable (X) is provided.   SSE = 6 SST = 16 Refer to Exhibit 12-4. The coefficient of correlation is</strong> A)0.7906 B)- 0.7906 C)0.625 D)0.375 SSE = 6
SST = 16
Refer to Exhibit 12-4. The coefficient of correlation is

A)0.7906
B)- 0.7906
C)0.625
D)0.375
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62
Exhibit 12-6
You are given the following information about y and x.
<strong>Exhibit 12-6 You are given the following information about y and x.   Refer to Exhibit 12-6. The least squares estimate of b<sub>0</sub> equals</strong> A)1 B)-1 C)-11 D)11
Refer to Exhibit 12-6. The least squares estimate of b0 equals

A)1
B)-1
C)-11
D)11
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63
Exhibit 12-6
You are given the following information about y and x.
<strong>Exhibit 12-6 You are given the following information about y and x.   Refer to Exhibit 12-6. The coefficient of determination equals</strong> A)-0.4364 B)0.4364 C)-0.1905 D)0.1905
Refer to Exhibit 12-6. The coefficient of determination equals

A)-0.4364
B)0.4364
C)-0.1905
D)0.1905
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64
Exhibit 12-5
You are given the following information about y and x.
<strong>Exhibit 12-5 You are given the following information about y and x.   Refer to Exhibit 12-5. The point estimate of y when x = 10 is</strong> A)-10 B)10 C)-4 D)4
Refer to Exhibit 12-5. The point estimate of y when x = 10 is

A)-10
B)10
C)-4
D)4
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65
Exhibit 12-3
Regression analysis was applied between sales data (in $1,000s) and advertising data (in $100s) and the following information was obtained.
<strong>Exhibit 12-3 Regression analysis was applied between sales data (in $1,000s) and advertising data (in $100s) and the following information was obtained.   Refer to Exhibit 12-3. Based on the above estimated regression equation, if advertising is $3,000, then the point estimate for sales (in dollars) is</strong> A)$66,000 B)$5,412 C)$66 D)$17,400
Refer to Exhibit 12-3. Based on the above estimated regression equation, if advertising is $3,000, then the point estimate for sales (in dollars) is

A)$66,000
B)$5,412
C)$66
D)$17,400
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66
Exhibit 12-4
The following information regarding a dependent variable (Y) and an independent variable (X) is provided.
<strong>Exhibit 12-4 The following information regarding a dependent variable (Y) and an independent variable (X) is provided.   SSE = 6 SST = 16 Refer to Exhibit 12-4. The coefficient of determination is</strong> A)0.7096 B)- 0.7906 C)0.625 D)0.375 SSE = 6
SST = 16
Refer to Exhibit 12-4. The coefficient of determination is

A)0.7096
B)- 0.7906
C)0.625
D)0.375
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67
Exhibit 12-6
You are given the following information about y and x.
<strong>Exhibit 12-6 You are given the following information about y and x.   Refer to Exhibit 12-6. The sample correlation coefficient equals</strong> A)-0.4364 B)0.4364 C)-0.1905 D)0.1905
Refer to Exhibit 12-6. The sample correlation coefficient equals

A)-0.4364
B)0.4364
C)-0.1905
D)0.1905
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68
Exhibit 12-5
You are given the following information about y and x.
<strong>Exhibit 12-5 You are given the following information about y and x.   Refer to Exhibit 12-5. The sample correlation coefficient equals</strong> A)0 B)+1 C)-1 D)-0.5
Refer to Exhibit 12-5. The sample correlation coefficient equals

A)0
B)+1
C)-1
D)-0.5
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69
Exhibit 12-6
You are given the following information about y and x.
<strong>Exhibit 12-6 You are given the following information about y and x.   Refer to Exhibit 12-6. The least squares estimate of b<sub>1</sub> equals</strong> A)1 B)-1 C)-11 D)11
Refer to Exhibit 12-6. The least squares estimate of b1 equals

A)1
B)-1
C)-11
D)11
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70
Exhibit 12-3
Regression analysis was applied between sales data (in $1,000s) and advertising data (in $100s) and the following information was obtained.
<strong>Exhibit 12-3 Regression analysis was applied between sales data (in $1,000s) and advertising data (in $100s) and the following information was obtained.   Refer to Exhibit 12-3. The t statistic for testing the significance of the slope is</strong> A)1.80 B)1.96 C)6.709 D)0.555
Refer to Exhibit 12-3. The t statistic for testing the significance of the slope is

A)1.80
B)1.96
C)6.709
D)0.555
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71
Exhibit 12-5
You are given the following information about y and x.
<strong>Exhibit 12-5 You are given the following information about y and x.   Refer to Exhibit 12-5. The coefficient of determination equals</strong> A)0 B)-1 C)+1 D)-0.5
Refer to Exhibit 12-5. The coefficient of determination equals

A)0
B)-1
C)+1
D)-0.5
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72
Given below are seven observations collected in a regression study on two variables, x (independent variable) and y (dependent variable).
Given below are seven observations collected in a regression study on two variables, x (independent variable) and y (dependent variable).   a.Develop the least squares estimated regression equation. b.At 95% confidence, perform a t test and determine whether or not the slope is significantly different from zero. c.Perform an F test to determine whether or not the model is significant. Let <font face=symbol></font> <font face=symbol></font> 0.05. d.Compute the coefficient of determination.
a.Develop the least squares estimated regression equation.
b.At 95% confidence, perform a t test and determine whether or not the slope is significantly different from zero.
c.Perform an F test to determine whether or not the model is significant. Let 0.05.
d.Compute the coefficient of determination.
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73
Exhibit 12-4
The following information regarding a dependent variable (Y) and an independent variable (X) is provided.
<strong>Exhibit 12-4 The following information regarding a dependent variable (Y) and an independent variable (X) is provided.   SSE = 6 SST = 16 Refer to Exhibit 12-4. The least squares estimate of the slope is</strong> A)1 B)2 C)3 D)4 SSE = 6
SST = 16
Refer to Exhibit 12-4. The least squares estimate of the slope is

A)1
B)2
C)3
D)4
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74
Exhibit 12-3
Regression analysis was applied between sales data (in $1,000s) and advertising data (in $100s) and the following information was obtained.
<strong>Exhibit 12-3 Regression analysis was applied between sales data (in $1,000s) and advertising data (in $100s) and the following information was obtained.   Refer to Exhibit 12-3. The F statistic computed from the above data is</strong> A)3 B)45 C)48 D)Not enough information is given to answer this question.
Refer to Exhibit 12-3. The F statistic computed from the above data is

A)3
B)45
C)48
D)Not enough information is given to answer this question.
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75
Exhibit 12-5
You are given the following information about y and x.
<strong>Exhibit 12-5 You are given the following information about y and x.   Refer to Exhibit 12-5. The least squares estimate of b<sub>0</sub> (intercept)equals</strong> A)1 B)-1 C)6 D)5
Refer to Exhibit 12-5. The least squares estimate of b0 (intercept)equals

A)1
B)-1
C)6
D)5
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76
Exhibit 12-4
The following information regarding a dependent variable (Y) and an independent variable (X) is provided.
<strong>Exhibit 12-4 The following information regarding a dependent variable (Y) and an independent variable (X) is provided.   SSE = 6 SST = 16 Refer to Exhibit 12-4. The MSE is</strong> A)1 B)2 C)3 D)4 SSE = 6
SST = 16
Refer to Exhibit 12-4. The MSE is

A)1
B)2
C)3
D)4
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77
Exhibit 12-3
Regression analysis was applied between sales data (in $1,000s) and advertising data (in $100s) and the following information was obtained.
 <strong>Exhibit 12-3 Regression analysis was applied between sales data (in $1,000s) and advertising data (in $100s) and the following information was obtained.    -Refer to Exhibit 12-3. The critical F value at  \alpha =0.05 is</strong> A)3.59 B)3.68 C)4.45 D)4.54

-Refer to Exhibit 12-3. The critical F value at α\alpha =0.05 is

A)3.59
B)3.68
C)4.45
D)4.54
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78
Exhibit 12-3
Regression analysis was applied between sales data (in $1,000s) and advertising data (in $100s) and the following information was obtained.
 <strong>Exhibit 12-3 Regression analysis was applied between sales data (in $1,000s) and advertising data (in $100s) and the following information was obtained.    -Refer to Exhibit 12-3. Using  \alpha  =0.05, the critical t value for testing the significance of the slope is</strong> A)1.753 B)2.131 C)1.746 D)2.120

-Refer to Exhibit 12-3. Using α\alpha =0.05, the critical t value for testing the significance of the slope is

A)1.753
B)2.131
C)1.746
D)2.120
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79
Exhibit 12-4
The following information regarding a dependent variable (Y) and an independent variable (X) is provided.
<strong>Exhibit 12-4 The following information regarding a dependent variable (Y) and an independent variable (X) is provided.   SSE = 6 SST = 16 Refer to Exhibit 12-4. The least squares estimate of the Y intercept is</strong> A)1 B)2 C)3 D)4 SSE = 6
SST = 16
Refer to Exhibit 12-4. The least squares estimate of the Y intercept is

A)1
B)2
C)3
D)4
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80
Exhibit 12-5
You are given the following information about y and x.
<strong>Exhibit 12-5 You are given the following information about y and x.   Refer to Exhibit 12-5. The least squares estimate of b<sub>1</sub> (slope) equals</strong> A)1 B)-1 C)6 D)5
Refer to Exhibit 12-5. The least squares estimate of b1 (slope) equals

A)1
B)-1
C)6
D)5
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Unlock Deck
Unlock for access to all 107 flashcards in this deck.