Deck 14: Simple Linear Regression

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Question
The standard error of the estimate is the

A) standard deviation of t.
B) square root of SSE.
C) square root of SST.
D) square root of MSE.
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Question
In the following estimated regression equation <strong>In the following estimated regression equation   = b<sub>0</sub> + b<sub>1</sub>x,</strong> A) b<sub>1</sub> is the slope. B) b<sub>1</sub> is the intercept. C) b<sub>1</sub>x is the slope. D) b<sub>1</sub>x is the intercept. <div style=padding-top: 35px> = b0 + b1x,

A) b1 is the slope.
B) b1 is the intercept.
C) b1x is the slope.
D) b1x is the intercept.
Question
In a regression analysis, the standard error of the estimate is determined to be 4. In this situation, the MSE

A) is 2.
B) is 16.
C) depends on the sample size.
D) requires a known SSE.
Question
The value of the coefficient of correlation (r)

A) can be equal to the value of the coefficient of determination (r2).
B) can never be equal to the value of the coefficient of determination (r2).
C) is always smaller than the value of the coefficient of determination (r2).
D) is always larger than the value of the coefficient of determination (r2).
Question
The interval estimate of an individual value of y for a given value of x is the

A) prediction interval estimate.
B) confidence interval estimate.
C) average regression interval.
D) x versus y correlation interval.
Question
The coefficient of determination

A) cannot be negative.
B) is the square root of the coefficient of correlation.
C) is the same as the coefficient of correlation.
D) can be negative or positive.
Question
The model developed from sample data that has the form of <strong>The model developed from sample data that has the form of   = b<sub>0</sub> + b<sub>1</sub>x is known as the</strong> A) regression equation. B) correlation model. C) estimated regression equation. D) regression model. <div style=padding-top: 35px> = b0 + b1x is known as the

A) regression equation.
B) correlation model.
C) estimated regression equation.
D) regression model.
Question
In regression analysis, the model in the form y = <strong>In regression analysis, the model in the form y =   +   x + ε is called the</strong> A) regression equation. B) correlation model. C) estimated regression equation. D) regression model <div style=padding-top: 35px> + <strong>In regression analysis, the model in the form y =   +   x + ε is called the</strong> A) regression equation. B) correlation model. C) estimated regression equation. D) regression model <div style=padding-top: 35px> x + ε is called the

A) regression equation.
B) correlation model.
C) estimated regression equation.
D) regression model
Question
The coefficient of correlation

A) is the square of the r-square.
B) is the square root of the r-square.
C) can never be equal to r-square.
D) can never be negative.
Question
The interval estimate of the mean value of y for a given value of x is the

A) prediction interval estimate.
B) confidence interval estimate.
C) average regression interval.
D) x versus y correlation interval.
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: ​   = 30,000 + 5x ​ The above equation implies that an</strong> A) increase of $4 in advertising is associated with an increase of $5000 in sales. B) increase of $1 in advertising is associated with an increase of $5 in sales. C) increase of $1 in advertising is associated with an increase of $34,000 in sales. D) increase of $1 in advertising is associated with an increase of $5000 in sales. <div style=padding-top: 35px> = 30,000 + 5x

The above equation implies that an

A) increase of $4 in advertising is associated with an increase of $5000 in sales.
B) increase of $1 in advertising is associated with an increase of $5 in sales.
C) increase of $1 in advertising is associated with an increase of $34,000 in sales.
D) increase of $1 in advertising is associated with an increase of $5000 in sales.
Question
In regression analysis, which of the following assumptions is not true about the error term ε?

A) The expected value of the error term is one.
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) The error term is normally distributed.
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
In regression analysis, the error term ε is a random variable with a mean or expected value of

A) 0.
B) 1.
C) μ.
D) <strong>In regression analysis, the error term ε is a random variable with a mean or expected value of</strong> A) 0. B) 1. C) μ. D)   . <div style=padding-top: 35px> .
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) one dependent, one independent, and several error variables are related.
Question
If only MSE is known, you can compute the

A) r-square.
B) coefficient of correlation.
C) standard error.
D) ith residual.
Question
In simple linear regression, r2 is the​

A) ​mean square error.
B) ​correlation coefficient.
C) squared residual.
D) ​coefficient of determination.
Question
The mathematical equation relating the independent variable to the expected value of the dependent variable; that is, E(y) = β0 + β1x, is known as the

A) regression equation.
B) correlation model.
C) estimated regression equation.
D) regression model.
Question
If the coefficient of determination is a positive value, then the coefficient of correlation

A) must also be positive.
B) must be zero.
C) can be either positive or negative.
D) can be larger than 1.
Question
In regression analysis, the unbiased estimate of the variance is

A) coefficient of correlation.
B) coefficient of determination.
C) mean square error.
D) slope of the regression equation.
Question
In regression analysis, the independent variable is

A) used to predict other independent variables.
B) used to predict the dependent variable.
C) the variable that is not used for prediction.
D) the variable that is being predicted.
Question
If the coefficient of determination is equal to 1, then the coefficient of correlation

A) must also be +1.
B) can be either -1 or +1.
C) can be any value between -1 to +1.
D) must be -1.
Question
In a regression analysis, the coefficient of determination is .4225. The coefficient of correlation in this situation is

A) -.65 if b1 is negative.
B) .1785.
C) .18 if b1 is positive.
D) .4225.
Question
In simple linear regression analysis, which of the following is not true?

A) The F test and the t test yield the same conclusion.
B) The F test and the t test may or may not yield the same conclusion.
C) The relationship between x and y is represented by a straight line.
D) The value of F = t2.
Question
In a regression and correlation analysis, if r2 = 1, then

A) SSE = SST.
B) SSE = 1.
C) SSR = SSE.
D) SSR = SST.
Question
If there is a very weak correlation between two variables, then the coefficient of determination must be

A) much larger than 1, if the correlation is positive.
B) much smaller than -1, if the correlation is negative.
C) equal to one.
D) closer or equal to zero.
Question
In a regression analysis, if SSE = 200 and SSR = 400, then the coefficient of determination is

A) .67.
B) .50.
C) .40.
D) .20.
Question
In a regression and correlation 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
If the coefficient of correlation is .8, the percentage of variation in the dependent variable explained by the variation in the independent variable is

A) .85%.
B) 85%.
C) .7225%.
D) 72.25%.
Question
In a regression analysis, the regression equation is given by y = 12 - 6x. If SSE = 510 and SST = 1000, then the coefficient of correlation is

A) -.7.
B) +.7.
C) .49.
D) -.49.
Question
?Which of the following is correct?

A) ?SSE = SSR +SST
B) ?SSR = SSE + SST
C) ?SST = SSR +SSE
D) ?SST = SSR - SSE
Question
In regression analysis, the variable that is being predicted is the

A) dependent variable.
B) independent variable.
C) intercept variable.
D) error variable.
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 regression line can be computed.
C) y-intercept can be computed.
D) x-intercept can be computed.
Question
In regression analysis, if the independent variable is measured in pounds, the dependent variable

A) must also be in pounds.
B) must be in some unit of weight.
C) cannot be in pounds.
D) can be measured in any units.
Question
Regression analysis was applied between demand for a product (y) and the price of the product (x), and the following estimated regression equation was obtained. ​ <strong>Regression analysis was applied between demand for a product (y) and the price of the product (x), and the following estimated regression equation was obtained. ​   = 120 - 10x ​ Based on the above estimated regression equation, if price is increased by 3units, then demand is expected to</strong> A) increase by 120 units. B) decrease by 100 units. C) increase by 30 units. D) decease by 30 units. <div style=padding-top: 35px> = 120 - 10x

Based on the above estimated regression equation, if price is increased by 3units, then demand is expected to

A) increase by 120 units.
B) decrease by 100 units.
C) increase by 30 units.
D) decease by 30 units.
Question
In a regression analysis, the coefficient of correlation is .15. The coefficient of determination in this situation is

A) .3873.
B) .0225.
C) 4.00.
D) 2.56.
Question
Correlation analysis is used to determine

A) the equation of the regression line.
B) the strength of the linear relationship between the dependent and the independent variables.
C) a specific value of the dependent variable for a given value of the independent variable.
D) a cause-and-effect relationship between the dependent and the independent variables.
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
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) estimation analysis.
Question
In a simple linear 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) if x is increased, y must also increase.
C) if y is increased, x must also increase.
D) the estimated regression line intercepts the positive y-axis.
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) easy to determine.
Question
If the coefficient of correlation is .4, then the slope of the regression line

A) must also be .4.
B) can be either negative or positive.
C) must be positive.
D) must be .16.
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) will be positive.
Question
It is possible for the coefficient of determination to be

A) larger than 1.
B) less than 1.
C) less than -1.
D) equal to -1.
Question
SSE can never be

A) larger than SST.
B) smaller than SST.
C) equal to one.
D) equal to zero.
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 - 4x ​ The above equation implies that if the price is increased by $1, the demand is expected to</strong> A) increase by 5 units. B) decrease by 4 units. C) decrease by 5000 units. D) decrease by 4000 units. <div style=padding-top: 35px> = 9 - 4x

The above equation implies that if the price is increased by $1, the demand is expected to

A) increase by 5 units.
B) decrease by 4 units.
C) decrease by 5000 units.
D) decrease by 4000 units.
Question
In a regression analysis, if SST = 500 and SSE = 200, then the coefficient of determination is

A) .20.
B) .67.
C) .60.
D) .40.
Question
Regression analysis was applied between sales (in $10,000) and advertising (in $100) and the following regression function was obtained. ​ <strong>Regression analysis was applied between sales (in $10,000) and advertising (in $100) and the following regression function was obtained. ​   = 50 + 8x ​ Based on the above estimated regression line, if advertising is $1000, then the point estimate for sales (in dollars) is</strong> A) $8050. B) $130. C) $130,000. D) $1,300,000. <div style=padding-top: 35px> = 50 + 8x

Based on the above estimated regression line, if advertising is $1000, then the point estimate for sales (in dollars) is

A) $8050.
B) $130.
C) $130,000.
D) $1,300,000.
Question
If a data set produces SSR = 300 and SSE = 200, then the coefficient of determination is

A) .67.
B) .25.
C) .40.
D) .60.
Question
In a regression analysis, if SST = 4500 and SSR = 2925, then the coefficient of determination is

A) .35.
B) .65.
C) .85.
D) .45.
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: ​   = 40 - 6x ​ The above equation implies that an</strong> A) increase of $1 in price is associated with a decrease of $6 in sales. B) increase of $8 in price is associated with a decrease of $24,000 in sales. C) increase of $1 in price is associated with a decrease of $240 in sales. D) increase of $1 in price is associated with a decrease of $6000 in sales. <div style=padding-top: 35px> = 40 - 6x

The above equation implies that an

A) increase of $1 in price is associated with a decrease of $6 in sales.
B) increase of $8 in price is associated with a decrease of $24,000 in sales.
C) increase of $1 in price is associated with a decrease of $240 in sales.
D) increase of $1 in price is associated with a decrease of $6000 in sales.
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) the F test is used to conclude there is a causal relationship between x and y.
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.
Question
A least squares regression line

A) can be used to predict a value of y if the corresponding x value is given.
B) implies a cause-and-effect relationship between x and y.
C) can only be determined if a good linear relationship exists between x and y.
D) ensures that the predictions of y outside the range of the values of x are valid.
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 these data

A) is 0.
B) is 1.
C) is 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 correlation is a negative value, then the

A) intercept of the regression line must also be positive.
B) coefficient of determination can be either a negative or a positive value, depending on the slope.
C) regression equation could have either a positive or a negative slope.
D) slope of the regression line must be negative.
Question
If there is a very strong correlation between two variables, then the coefficient of determination must be

A) much larger than 1, if the correlation is positive.
B) much smaller than -1, if the correlation is negative.
C) equal to zero.
D) closer or equal to 1.
Question
If the coefficient of correlation is .80, then the coefficient of determination

A) is also .80.
B) is either .64 or -.64.
C) will be -.80.
D) must be .64.
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 units of currency.
C) can be measured in any units.
D) cannot be in dollars.
Question
If the coefficient of correlation is .4, the percentage of variation in the dependent variable explained by the variation in the independent variable is

A) 40%.
B) 16%.
C) 4%.
D) 63%.
Question
Regression analysis was applied between sales data (y in $1000s) and advertising data (x in $100s) and the following information was obtained. ​ <strong>Regression analysis was applied between sales data (y in $1000s) and advertising data (x in $100s) and the following information was obtained. ​   = 12 + 1.8x ​ N = 17 SSR = 225 SSE = 75 Sb<sub>1</sub> = .2683 The t statistic for testing the significance of the slope is</strong> A) 1.80. B) 1.96. C) 6.71. D) .56. <div style=padding-top: 35px> = 12 + 1.8x

N = 17
SSR = 225
SSE = 75
Sb1 = .2683
The t statistic for testing the significance of the slope is

A) 1.80.
B) 1.96.
C) 6.71.
D) .56.
Question
Regression analysis was applied between sales (y in $1000) and advertising (x in $100) and the following estimated regression equation was obtained. ​ <strong>Regression analysis was applied between sales (y in $1000) and advertising (x in $100) and the following estimated regression equation 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
You are given the following information about y and x. <strong>You are given the following information about y and x.   ​ The least squares estimate of the slope or b<sub>1</sub> equals</strong> A) 1. B) -1. C) -10.75. D) 10.75. <div style=padding-top: 35px> ​ The least squares estimate of the slope or b1 equals

A) 1.
B) -1.
C) -10.75.
D) 10.75.
Question
You are given the following information about y and x. <strong>You are given the following information about y and x.   ​ The sample correlation coefficient equals</strong> A) 0. B) +1. C) -1. D) -.5. <div style=padding-top: 35px> ​ The sample correlation coefficient equals

A) 0.
B) +1.
C) -1.
D) -.5.
Question
The following information regarding a dependent variable (y) and an independent variable (x) is provided. ​ <strong>The following information regarding a dependent variable (y) and an independent variable (x) is provided. ​   ​ SSE = 1.9 SST = 6.8 ​ The least squares estimate of the slope is</strong> A) 1. B) 3.4. C) 3. D) .7. <div style=padding-top: 35px>
SSE = 1.9
SST = 6.8

The least squares estimate of the slope is

A) 1.
B) 3.4.
C) 3.
D) .7.
Question
You are given the following information about y and x. <strong>You are given the following information about y and x.   ​ The sample correlation coefficient equals</strong> A) -.7303. B) .7303. C) -.5333. D) .5333. <div style=padding-top: 35px> ​ The sample correlation coefficient equals

A) -.7303.
B) .7303.
C) -.5333.
D) .5333.
Question
The following information regarding a dependent variable (y) and an independent variable (x) is provided. <strong>The following information regarding a dependent variable (y) and an independent variable (x) is provided.   ​ SSE = 1.9 SST = 6.8 ​ The least squares estimate of the y-intercept is</strong> A) 1. B) 3.4. C) 3. D) 4.7. <div style=padding-top: 35px> ​ SSE = 1.9
SST = 6.8

The least squares estimate of the y-intercept is

A) 1.
B) 3.4.
C) 3.
D) 4.7.
Question
If the coefficient of determination is .95, the percentage of variation in the dependent variable explained by the variation in the independent variable is

A) .95%.
B) 95%.
C) 90.25%.
D) .9025%.
Question
The following information regarding a dependent variable (y) and an independent variable (x) is provided. <strong>The following information regarding a dependent variable (y) and an independent variable (x) is provided.   ​ SSE = 1.9 SST = 6.8 ​ The MSE is</strong> A) 4.9. B) .63. C) 6.8. D) 1.9. <div style=padding-top: 35px> ​ SSE = 1.9
SST = 6.8

The MSE is

A) 4.9.
B) .63.
C) 6.8.
D) 1.9.
Question
You are given the following information about y and x. <strong>You are given the following information about y and x.   ​ The point estimate of y when x = 2 is</strong> A) -10. B) 10. C) -8. D) 8. <div style=padding-top: 35px> ​ The point estimate of y when x = 2 is

A) -10.
B) 10.
C) -8.
D) 8.
Question
Regression analysis was applied between sales data (y in $1000s) and advertising data (x in $100s) and the following information was obtained. ​ <strong>Regression analysis was applied between sales data (y in $1000s) and advertising data (x in $100s) and the following information was obtained. ​   = 12 + 1.8x ​ N = 17 SSR = 225 SSE = 75 Sb<sub>1</sub> = .2683 ​ To perform an F test, the p-value is</strong> A) less than .01. B) between .01 and .025. C) between .025 and .05. D) greater than .10. <div style=padding-top: 35px> = 12 + 1.8x

N = 17
SSR = 225
SSE = 75
Sb1 = .2683

To perform an F test, the p-value is

A) less than .01.
B) between .01 and .025.
C) between .025 and .05.
D) greater than .10.
Question
The following information regarding a dependent variable (y) and an independent variable (x) is provided. <strong>The following information regarding a dependent variable (y) and an independent variable (x) is provided.   ​ SSE = 1.9 SST = 6.8 ​ The coefficient of determination is</strong> A) .8489. B) -.7206. C) .7206. D) .375. <div style=padding-top: 35px> ​ SSE = 1.9
SST = 6.8

The coefficient of determination is

A) .8489.
B) -.7206.
C) .7206.
D) .375.
Question
You are given the following information about y and x. <strong>You are given the following information about y and x.   ​ The least squares estimate of the slope or b<sub>1</sub> equals</strong> A) 1. B) -2. C) 3. D) 12. <div style=padding-top: 35px> ​ The least squares estimate of the slope or b1 equals

A) 1.
B) -2.
C) 3.
D) 12.
Question
Regression analysis was applied between sales data (y in $1000s) and advertising data (x in $100s) and the following information was obtained. ​ <strong>Regression analysis was applied between sales data (y in $1000s) and advertising data (x in $100s) and the following information was obtained. ​   = 12 + 1.8x ​ N = 17 SSR = 225 SSE = 75 Sb<sub>1</sub> = .2683 ​ Based on the above estimated regression equation, if advertising is $3000, then the point estimate for sales (in dollars) is</strong> A) $66,000. B) $5412. C) $66. D) $17,400. <div style=padding-top: 35px> = 12 + 1.8x

N = 17
SSR = 225
SSE = 75
Sb1 = .2683

Based on the above estimated regression equation, if advertising is $3000, then the point estimate for sales (in dollars) is

A) $66,000.
B) $5412.
C) $66.
D) $17,400.
Question
Regression analysis was applied between sales data (y in $1000s) and advertising data (x in $100s) and the following information was obtained. ​ <strong>Regression analysis was applied between sales data (y in $1000s) and advertising data (x in $100s) and the following information was obtained. ​   = 12 + 1.8x ​ N = 17 SSR = 225 SSE = 75 Sb<sub>1</sub> = .2683 The F statistic computed from the above data is</strong> A) 3. B) 45. C) 48. D) 50. <div style=padding-top: 35px> = 12 + 1.8x

N = 17
SSR = 225
SSE = 75
Sb1 = .2683
The F statistic computed from the above data is

A) 3.
B) 45.
C) 48.
D) 50.
Question
You are given the following information about y and x. <strong>You are given the following information about y and x.   ​ The coefficient of determination equals</strong> A) 0. B) -1. C) +1. D) -.5. <div style=padding-top: 35px> ​ The coefficient of determination equals

A) 0.
B) -1.
C) +1.
D) -.5.
Question
The following information regarding a dependent variable (y) and an independent variable (x) is provided. <strong>The following information regarding a dependent variable (y) and an independent variable (x) is provided.   ​ SSE = 1.9 SST = 6.8 ​ The coefficient of correlation is</strong> A) .8489. B) -.7206. C) .7206. D) .375. <div style=padding-top: 35px> ​ SSE = 1.9
SST = 6.8

The coefficient of correlation is

A) .8489.
B) -.7206.
C) .7206.
D) .375.
Question
You are given the following information about y and x. ​ <strong>You are given the following information about y and x. ​   ​ The least squares estimate of the intercept or b<sub>0</sub> equals</strong> A) 1. B) -2. C) 12. D) 4. <div style=padding-top: 35px>
The least squares estimate of the intercept or b0 equals

A) 1.
B) -2.
C) 12.
D) 4.
Question
You are given the following information about y and x. <strong>You are given the following information about y and x.   ​ The coefficient of determination equals</strong> A) -.7303. B) .7303. C) -.5333. D) .5333. <div style=padding-top: 35px> ​ The coefficient of determination equals

A) -.7303.
B) .7303.
C) -.5333.
D) .5333.
Question
You are given the following information about y and x. <strong>You are given the following information about y and x.   ​ The least squares estimate of the intercept or b<sub>0</sub> equals</strong> A) 1. B) -1. C) -10.75. D) 10.75. <div style=padding-top: 35px> ​ The least squares estimate of the intercept or b0 equals

A) 1.
B) -1.
C) -10.75.
D) 10.75.
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Deck 14: Simple Linear Regression
1
The standard error of the estimate is the

A) standard deviation of t.
B) square root of SSE.
C) square root of SST.
D) square root of MSE.
square root of MSE.
2
In the following estimated regression equation <strong>In the following estimated regression equation   = b<sub>0</sub> + b<sub>1</sub>x,</strong> A) b<sub>1</sub> is the slope. B) b<sub>1</sub> is the intercept. C) b<sub>1</sub>x is the slope. D) b<sub>1</sub>x is the intercept. = b0 + b1x,

A) b1 is the slope.
B) b1 is the intercept.
C) b1x is the slope.
D) b1x is the intercept.
b1 is the slope.
3
In a regression analysis, the standard error of the estimate is determined to be 4. In this situation, the MSE

A) is 2.
B) is 16.
C) depends on the sample size.
D) requires a known SSE.
is 16.
4
The value of the coefficient of correlation (r)

A) can be equal to the value of the coefficient of determination (r2).
B) can never be equal to the value of the coefficient of determination (r2).
C) is always smaller than the value of the coefficient of determination (r2).
D) is always larger than the value of the coefficient of determination (r2).
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5
The interval estimate of an individual value of y for a given value of x is the

A) prediction interval estimate.
B) confidence interval estimate.
C) average regression interval.
D) x versus y correlation interval.
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6
The coefficient of determination

A) cannot be negative.
B) is the square root of the coefficient of correlation.
C) is the same as the coefficient of correlation.
D) can be negative or positive.
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7
The model developed from sample data that has the form of <strong>The model developed from sample data that has the form of   = b<sub>0</sub> + b<sub>1</sub>x is known as the</strong> A) regression equation. B) correlation model. C) estimated regression equation. D) regression model. = b0 + b1x is known as the

A) regression equation.
B) correlation model.
C) estimated regression equation.
D) regression model.
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8
In regression analysis, the model in the form y = <strong>In regression analysis, the model in the form y =   +   x + ε is called the</strong> A) regression equation. B) correlation model. C) estimated regression equation. D) regression model + <strong>In regression analysis, the model in the form y =   +   x + ε is called the</strong> A) regression equation. B) correlation model. C) estimated regression equation. D) regression model x + ε is called the

A) regression equation.
B) correlation model.
C) estimated regression equation.
D) regression model
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9
The coefficient of correlation

A) is the square of the r-square.
B) is the square root of the r-square.
C) can never be equal to r-square.
D) can never be negative.
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10
The interval estimate of the mean value of y for a given value of x is the

A) prediction interval estimate.
B) confidence interval estimate.
C) average regression interval.
D) x versus y correlation interval.
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11
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: ​   = 30,000 + 5x ​ The above equation implies that an</strong> A) increase of $4 in advertising is associated with an increase of $5000 in sales. B) increase of $1 in advertising is associated with an increase of $5 in sales. C) increase of $1 in advertising is associated with an increase of $34,000 in sales. D) increase of $1 in advertising is associated with an increase of $5000 in sales. = 30,000 + 5x

The above equation implies that an

A) increase of $4 in advertising is associated with an increase of $5000 in sales.
B) increase of $1 in advertising is associated with an increase of $5 in sales.
C) increase of $1 in advertising is associated with an increase of $34,000 in sales.
D) increase of $1 in advertising is associated with an increase of $5000 in sales.
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12
In regression analysis, which of the following assumptions is not true about the error term ε?

A) The expected value of the error term is one.
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) The error term is normally distributed.
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13
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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14
In regression analysis, the error term ε is a random variable with a mean or expected value of

A) 0.
B) 1.
C) μ.
D) <strong>In regression analysis, the error term ε is a random variable with a mean or expected value of</strong> A) 0. B) 1. C) μ. D)   . .
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15
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) one dependent, one independent, and several error variables are related.
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16
If only MSE is known, you can compute the

A) r-square.
B) coefficient of correlation.
C) standard error.
D) ith residual.
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17
In simple linear regression, r2 is the​

A) ​mean square error.
B) ​correlation coefficient.
C) squared residual.
D) ​coefficient of determination.
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18
The mathematical equation relating the independent variable to the expected value of the dependent variable; that is, E(y) = β0 + β1x, is known as the

A) regression equation.
B) correlation model.
C) estimated regression equation.
D) regression model.
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19
If the coefficient of determination is a positive value, then the coefficient of correlation

A) must also be positive.
B) must be zero.
C) can be either positive or negative.
D) can be larger than 1.
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20
In regression analysis, the unbiased estimate of the variance is

A) coefficient of correlation.
B) coefficient of determination.
C) mean square error.
D) slope of the regression equation.
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21
In regression analysis, the independent variable is

A) used to predict other independent variables.
B) used to predict the dependent variable.
C) the variable that is not used for prediction.
D) the variable that is being predicted.
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22
If the coefficient of determination is equal to 1, then the coefficient of correlation

A) must also be +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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23
In a regression analysis, the coefficient of determination is .4225. The coefficient of correlation in this situation is

A) -.65 if b1 is negative.
B) .1785.
C) .18 if b1 is positive.
D) .4225.
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24
In simple linear regression analysis, which of the following is not true?

A) The F test and the t test yield the same conclusion.
B) The F test and the t test may or may not yield the same conclusion.
C) The relationship between x and y is represented by a straight line.
D) The value of F = t2.
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25
In a regression and correlation analysis, if r2 = 1, then

A) SSE = SST.
B) SSE = 1.
C) SSR = SSE.
D) SSR = SST.
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26
If there is a very weak correlation between two variables, then the coefficient of determination must be

A) much larger than 1, if the correlation is positive.
B) much smaller than -1, if the correlation is negative.
C) equal to one.
D) closer or equal to zero.
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27
In a regression analysis, if SSE = 200 and SSR = 400, then the coefficient of determination is

A) .67.
B) .50.
C) .40.
D) .20.
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28
In a regression and correlation 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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29
If the coefficient of correlation is .8, the percentage of variation in the dependent variable explained by the variation in the independent variable is

A) .85%.
B) 85%.
C) .7225%.
D) 72.25%.
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30
In a regression analysis, the regression equation is given by y = 12 - 6x. If SSE = 510 and SST = 1000, then the coefficient of correlation is

A) -.7.
B) +.7.
C) .49.
D) -.49.
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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 - SSE
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32
In regression analysis, the variable that is being predicted is the

A) dependent variable.
B) independent variable.
C) intercept variable.
D) error variable.
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33
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 regression line can be computed.
C) y-intercept can be computed.
D) x-intercept can be computed.
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34
In regression analysis, if the independent variable is measured in pounds, the dependent variable

A) must also be in pounds.
B) must be in some unit of weight.
C) cannot be in pounds.
D) can be measured in any units.
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35
Regression analysis was applied between demand for a product (y) and the price of the product (x), and the following estimated regression equation was obtained. ​ <strong>Regression analysis was applied between demand for a product (y) and the price of the product (x), and the following estimated regression equation was obtained. ​   = 120 - 10x ​ Based on the above estimated regression equation, if price is increased by 3units, then demand is expected to</strong> A) increase by 120 units. B) decrease by 100 units. C) increase by 30 units. D) decease by 30 units. = 120 - 10x

Based on the above estimated regression equation, if price is increased by 3units, then demand is expected to

A) increase by 120 units.
B) decrease by 100 units.
C) increase by 30 units.
D) decease by 30 units.
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36
In a regression analysis, the coefficient of correlation is .15. The coefficient of determination in this situation is

A) .3873.
B) .0225.
C) 4.00.
D) 2.56.
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37
Correlation analysis is used to determine

A) the equation of the regression line.
B) the strength of the linear relationship between the dependent and the independent variables.
C) a specific value of the dependent variable for a given value of the independent variable.
D) a cause-and-effect relationship between the dependent and the independent variables.
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38
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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39
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) estimation analysis.
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40
In a simple linear 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) if x is increased, y must also increase.
C) if y is increased, x must also increase.
D) the estimated regression line intercepts the positive y-axis.
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41
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) easy to determine.
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42
If the coefficient of correlation is .4, then the slope of the regression line

A) must also be .4.
B) can be either negative or positive.
C) must be positive.
D) must be .16.
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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) will be positive.
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44
It is possible for the coefficient of determination to be

A) larger than 1.
B) less than 1.
C) less than -1.
D) equal to -1.
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45
SSE can never be

A) larger than SST.
B) smaller than SST.
C) equal to one.
D) equal to zero.
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46
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 - 4x ​ The above equation implies that if the price is increased by $1, the demand is expected to</strong> A) increase by 5 units. B) decrease by 4 units. C) decrease by 5000 units. D) decrease by 4000 units. = 9 - 4x

The above equation implies that if the price is increased by $1, the demand is expected to

A) increase by 5 units.
B) decrease by 4 units.
C) decrease by 5000 units.
D) decrease by 4000 units.
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47
In a regression analysis, if SST = 500 and SSE = 200, then the coefficient of determination is

A) .20.
B) .67.
C) .60.
D) .40.
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48
Regression analysis was applied between sales (in $10,000) and advertising (in $100) and the following regression function was obtained. ​ <strong>Regression analysis was applied between sales (in $10,000) and advertising (in $100) and the following regression function was obtained. ​   = 50 + 8x ​ Based on the above estimated regression line, if advertising is $1000, then the point estimate for sales (in dollars) is</strong> A) $8050. B) $130. C) $130,000. D) $1,300,000. = 50 + 8x

Based on the above estimated regression line, if advertising is $1000, then the point estimate for sales (in dollars) is

A) $8050.
B) $130.
C) $130,000.
D) $1,300,000.
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49
If a data set produces SSR = 300 and SSE = 200, then the coefficient of determination is

A) .67.
B) .25.
C) .40.
D) .60.
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50
In a regression analysis, if SST = 4500 and SSR = 2925, then the coefficient of determination is

A) .35.
B) .65.
C) .85.
D) .45.
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51
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: ​   = 40 - 6x ​ The above equation implies that an</strong> A) increase of $1 in price is associated with a decrease of $6 in sales. B) increase of $8 in price is associated with a decrease of $24,000 in sales. C) increase of $1 in price is associated with a decrease of $240 in sales. D) increase of $1 in price is associated with a decrease of $6000 in sales. = 40 - 6x

The above equation implies that an

A) increase of $1 in price is associated with a decrease of $6 in sales.
B) increase of $8 in price is associated with a decrease of $24,000 in sales.
C) increase of $1 in price is associated with a decrease of $240 in sales.
D) increase of $1 in price is associated with a decrease of $6000 in sales.
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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) the F test is used to conclude there is a causal relationship between x and y.
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53
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.
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54
A least squares regression line

A) can be used to predict a value of y if the corresponding x value is given.
B) implies a cause-and-effect relationship between x and y.
C) can only be determined if a good linear relationship exists between x and y.
D) ensures that the predictions of y outside the range of the values of x are valid.
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55
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 these data

A) is 0.
B) is 1.
C) is 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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56
If the coefficient of correlation is a negative value, then the

A) intercept of the regression line must also be positive.
B) coefficient of determination can be either a negative or a positive value, depending on the slope.
C) regression equation could have either a positive or a negative slope.
D) slope of the regression line must be negative.
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57
If there is a very strong correlation between two variables, then the coefficient of determination must be

A) much larger than 1, if the correlation is positive.
B) much smaller than -1, if the correlation is negative.
C) equal to zero.
D) closer or equal to 1.
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58
If the coefficient of correlation is .80, then the coefficient of determination

A) is also .80.
B) is either .64 or -.64.
C) will be -.80.
D) must be .64.
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59
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 units of currency.
C) can be measured in any units.
D) cannot be in dollars.
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60
If the coefficient of correlation is .4, the percentage of variation in the dependent variable explained by the variation in the independent variable is

A) 40%.
B) 16%.
C) 4%.
D) 63%.
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61
Regression analysis was applied between sales data (y in $1000s) and advertising data (x in $100s) and the following information was obtained. ​ <strong>Regression analysis was applied between sales data (y in $1000s) and advertising data (x in $100s) and the following information was obtained. ​   = 12 + 1.8x ​ N = 17 SSR = 225 SSE = 75 Sb<sub>1</sub> = .2683 The t statistic for testing the significance of the slope is</strong> A) 1.80. B) 1.96. C) 6.71. D) .56. = 12 + 1.8x

N = 17
SSR = 225
SSE = 75
Sb1 = .2683
The t statistic for testing the significance of the slope is

A) 1.80.
B) 1.96.
C) 6.71.
D) .56.
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62
Regression analysis was applied between sales (y in $1000) and advertising (x in $100) and the following estimated regression equation was obtained. ​ <strong>Regression analysis was applied between sales (y in $1000) and advertising (x in $100) and the following estimated regression equation 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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63
You are given the following information about y and x. <strong>You are given the following information about y and x.   ​ The least squares estimate of the slope or b<sub>1</sub> equals</strong> A) 1. B) -1. C) -10.75. D) 10.75. ​ The least squares estimate of the slope or b1 equals

A) 1.
B) -1.
C) -10.75.
D) 10.75.
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64
You are given the following information about y and x. <strong>You are given the following information about y and x.   ​ The sample correlation coefficient equals</strong> A) 0. B) +1. C) -1. D) -.5. ​ The sample correlation coefficient equals

A) 0.
B) +1.
C) -1.
D) -.5.
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65
The following information regarding a dependent variable (y) and an independent variable (x) is provided. ​ <strong>The following information regarding a dependent variable (y) and an independent variable (x) is provided. ​   ​ SSE = 1.9 SST = 6.8 ​ The least squares estimate of the slope is</strong> A) 1. B) 3.4. C) 3. D) .7.
SSE = 1.9
SST = 6.8

The least squares estimate of the slope is

A) 1.
B) 3.4.
C) 3.
D) .7.
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66
You are given the following information about y and x. <strong>You are given the following information about y and x.   ​ The sample correlation coefficient equals</strong> A) -.7303. B) .7303. C) -.5333. D) .5333. ​ The sample correlation coefficient equals

A) -.7303.
B) .7303.
C) -.5333.
D) .5333.
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67
The following information regarding a dependent variable (y) and an independent variable (x) is provided. <strong>The following information regarding a dependent variable (y) and an independent variable (x) is provided.   ​ SSE = 1.9 SST = 6.8 ​ The least squares estimate of the y-intercept is</strong> A) 1. B) 3.4. C) 3. D) 4.7. ​ SSE = 1.9
SST = 6.8

The least squares estimate of the y-intercept is

A) 1.
B) 3.4.
C) 3.
D) 4.7.
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68
If the coefficient of determination is .95, the percentage of variation in the dependent variable explained by the variation in the independent variable is

A) .95%.
B) 95%.
C) 90.25%.
D) .9025%.
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69
The following information regarding a dependent variable (y) and an independent variable (x) is provided. <strong>The following information regarding a dependent variable (y) and an independent variable (x) is provided.   ​ SSE = 1.9 SST = 6.8 ​ The MSE is</strong> A) 4.9. B) .63. C) 6.8. D) 1.9. ​ SSE = 1.9
SST = 6.8

The MSE is

A) 4.9.
B) .63.
C) 6.8.
D) 1.9.
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70
You are given the following information about y and x. <strong>You are given the following information about y and x.   ​ The point estimate of y when x = 2 is</strong> A) -10. B) 10. C) -8. D) 8. ​ The point estimate of y when x = 2 is

A) -10.
B) 10.
C) -8.
D) 8.
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71
Regression analysis was applied between sales data (y in $1000s) and advertising data (x in $100s) and the following information was obtained. ​ <strong>Regression analysis was applied between sales data (y in $1000s) and advertising data (x in $100s) and the following information was obtained. ​   = 12 + 1.8x ​ N = 17 SSR = 225 SSE = 75 Sb<sub>1</sub> = .2683 ​ To perform an F test, the p-value is</strong> A) less than .01. B) between .01 and .025. C) between .025 and .05. D) greater than .10. = 12 + 1.8x

N = 17
SSR = 225
SSE = 75
Sb1 = .2683

To perform an F test, the p-value is

A) less than .01.
B) between .01 and .025.
C) between .025 and .05.
D) greater than .10.
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72
The following information regarding a dependent variable (y) and an independent variable (x) is provided. <strong>The following information regarding a dependent variable (y) and an independent variable (x) is provided.   ​ SSE = 1.9 SST = 6.8 ​ The coefficient of determination is</strong> A) .8489. B) -.7206. C) .7206. D) .375. ​ SSE = 1.9
SST = 6.8

The coefficient of determination is

A) .8489.
B) -.7206.
C) .7206.
D) .375.
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73
You are given the following information about y and x. <strong>You are given the following information about y and x.   ​ The least squares estimate of the slope or b<sub>1</sub> equals</strong> A) 1. B) -2. C) 3. D) 12. ​ The least squares estimate of the slope or b1 equals

A) 1.
B) -2.
C) 3.
D) 12.
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74
Regression analysis was applied between sales data (y in $1000s) and advertising data (x in $100s) and the following information was obtained. ​ <strong>Regression analysis was applied between sales data (y in $1000s) and advertising data (x in $100s) and the following information was obtained. ​   = 12 + 1.8x ​ N = 17 SSR = 225 SSE = 75 Sb<sub>1</sub> = .2683 ​ Based on the above estimated regression equation, if advertising is $3000, then the point estimate for sales (in dollars) is</strong> A) $66,000. B) $5412. C) $66. D) $17,400. = 12 + 1.8x

N = 17
SSR = 225
SSE = 75
Sb1 = .2683

Based on the above estimated regression equation, if advertising is $3000, then the point estimate for sales (in dollars) is

A) $66,000.
B) $5412.
C) $66.
D) $17,400.
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75
Regression analysis was applied between sales data (y in $1000s) and advertising data (x in $100s) and the following information was obtained. ​ <strong>Regression analysis was applied between sales data (y in $1000s) and advertising data (x in $100s) and the following information was obtained. ​   = 12 + 1.8x ​ N = 17 SSR = 225 SSE = 75 Sb<sub>1</sub> = .2683 The F statistic computed from the above data is</strong> A) 3. B) 45. C) 48. D) 50. = 12 + 1.8x

N = 17
SSR = 225
SSE = 75
Sb1 = .2683
The F statistic computed from the above data is

A) 3.
B) 45.
C) 48.
D) 50.
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76
You are given the following information about y and x. <strong>You are given the following information about y and x.   ​ The coefficient of determination equals</strong> A) 0. B) -1. C) +1. D) -.5. ​ The coefficient of determination equals

A) 0.
B) -1.
C) +1.
D) -.5.
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77
The following information regarding a dependent variable (y) and an independent variable (x) is provided. <strong>The following information regarding a dependent variable (y) and an independent variable (x) is provided.   ​ SSE = 1.9 SST = 6.8 ​ The coefficient of correlation is</strong> A) .8489. B) -.7206. C) .7206. D) .375. ​ SSE = 1.9
SST = 6.8

The coefficient of correlation is

A) .8489.
B) -.7206.
C) .7206.
D) .375.
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78
You are given the following information about y and x. ​ <strong>You are given the following information about y and x. ​   ​ The least squares estimate of the intercept or b<sub>0</sub> equals</strong> A) 1. B) -2. C) 12. D) 4.
The least squares estimate of the intercept or b0 equals

A) 1.
B) -2.
C) 12.
D) 4.
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79
You are given the following information about y and x. <strong>You are given the following information about y and x.   ​ The coefficient of determination equals</strong> A) -.7303. B) .7303. C) -.5333. D) .5333. ​ The coefficient of determination equals

A) -.7303.
B) .7303.
C) -.5333.
D) .5333.
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80
You are given the following information about y and x. <strong>You are given the following information about y and x.   ​ The least squares estimate of the intercept or b<sub>0</sub> equals</strong> A) 1. B) -1. C) -10.75. D) 10.75. ​ The least squares estimate of the intercept or b0 equals

A) 1.
B) -1.
C) -10.75.
D) 10.75.
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Unlock Deck
Unlock for access to all 132 flashcards in this deck.