Question 1

To calculate the residual, you would take

Accepted Answer

A)  yi - 
      
B)    - yi 
C)  xi -   
D)  xi - 
      
A)  yi - 
      
B)    - yi 
C)  xi -   
D)  xi -

Question 2

The following information regarding a dependent variable y and an independent variable x is provided: Σx = 90
Σ(y -   )(x -   ) = -156
Σy = 340
Σ(x -   )2 = 234
N = 4
Σ(y -   )2 = 1974
SSR = 104
​
The coefficient of correlation is

Accepted Answer

A)  -.2295. 
B)  .2295. 
C)  .0572. 
D)  -.0572. 
A)  -.2295. 
B)  .2295. 
C)  .0572. 
D)  -.0572.

Question 3

If the coefficient of determination is a positive value, then the coefficient of correlation

Accepted Answer

A)  must also be positive. 
B)  must be zero. 
C)  can be either positive or negative. 
D)  can be larger than 1. 
A)  must also be positive. 
B)  must be zero. 
C)  can be either positive or negative. 
D)  can be larger than 1.

Question 4

Correlation analysis is used to determine

Accepted Answer

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. 
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 5

If the coefficient of correlation is a negative value, then the coefficient of determination

Accepted Answer

A)  must also be negative. 
B)  must be zero. 
C)  can be either negative or positive. 
D)  will be positive. 
A)  must also be negative. 
B)  must be zero. 
C)  can be either negative or positive. 
D)  will be positive.

Question 6

In simple linear regression, r2 is the​

Accepted Answer

A)  ​mean square error. 
B)  ​correlation coefficient. 
C)  squared residual. 
D)  ​coefficient of determination. 
A)  ​mean square error. 
B)  ​correlation coefficient. 
C)  squared residual. 
D)  ​coefficient of determination.

Question 7

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

Accepted Answer

A)  regression equation. 
B)  correlation model. 
C)  estimated regression equation. 
D)  regression model. 
A)  regression equation. 
B)  correlation model. 
C)  estimated regression equation. 
D)  regression model.

Question 8

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
Sb1 = .2683
The t statistic for testing the significance of the slope is

Accepted Answer

A)  1.80. 
B)  1.96. 
C)  6.71. 
D)  .56. 
A)  1.80. 
B)  1.96. 
C)  6.71. 
D)  .56.

Question 9

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
Sb1 = .2683
The F statistic computed from the above data is

Accepted Answer

A)  3. 
B)  45. 
C)  48. 
D)  50. 
A)  3. 
B)  45. 
C)  48. 
D)  50.

Question 10

In simple linear regression, r is the

Accepted Answer

A)  mean square error. 
B)  correlation coefficient. 
C)  squared residual. 
D)  coefficient of determination. 
A)  mean square error. 
B)  correlation coefficient. 
C)  squared residual. 
D)  coefficient of determination.

Question 11

In regression analysis, the variable that is being predicted is the

Accepted Answer

A)  dependent variable. 
B)  independent variable. 
C)  intercept variable. 
D)  error variable. 
A)  dependent variable. 
B)  independent variable. 
C)  intercept variable. 
D)  error variable.

Question 12

If the coefficient of determination is equal to 1, then the coefficient of correlation

Accepted Answer

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. 
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 13

The following information regarding a dependent variable y and an independent variable x is provided:   ​ The total sum of squares (SST) is

Accepted Answer

A)  -156. 
B)  234. 
C)  1870. 
D)  1974. 
A)  -156. 
B)  234. 
C)  1870. 
D)  1974.

Question 14

In regression analysis, if the dependent variable is measured in dollars, the independent variable

Accepted Answer

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. 
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 15

In a regression analysis, if SSE = 200 and SSR = 400, then the coefficient of determination is

Accepted Answer

A)  .67. 
B)  .50. 
C)  .40. 
D)  .20. 
A)  .67. 
B)  .50. 
C)  .40. 
D)  .20.

Question 16

SSE can never be

Accepted Answer

A)  larger than SST. 
B)  smaller than SST. 
C)  equal to one. 
D)  equal to zero. 
A)  larger than SST. 
B)  smaller than SST. 
C)  equal to one. 
D)  equal to zero.

Question 17

The following information regarding a dependent variable y and an independent variable x is provided:   ​ The y-intercept is

Accepted Answer

A)  -.667. 
B)  .667. 
C)  100. 
D)  -100. 
A)  -.667. 
B)  .667. 
C)  100. 
D)  -100.

Question 18

In the following estimated regression equation   = b0 + b1x,

Accepted Answer

A)  b1 is the slope. 
B)  b1 is the intercept. 
C)  b1x is the slope. 
D)  b1x is the intercept. 
A)  b1 is the slope. 
B)  b1 is the intercept. 
C)  b1x is the slope. 
D)  b1x is the intercept.

Question 19

The following information regarding a dependent variable y and an independent variable x is provided:   ​ The mean square error (MSE) is

Accepted Answer

A)  1870. 
B)  13. 
C)  1974. 
D)  935. 
A)  1870. 
B)  13. 
C)  1974. 
D)  935.

Question 20

It is not possible for the coefficient of determination to be

Accepted Answer

A)  larger than 1. 
B)  less than 1. 
C)  between 0 and 1. 
D)  equal to 1. 
A)  larger than 1. 
B)  less than 1. 
C)  between 0 and 1. 
D)  equal to 1.

Exam 14: Simple Linear Regression

To calculate the residual, you would take

The following information regarding a dependent variable y and an independent variable x is provided: Σx = 90 Σ(y - )(x - ) = -156 Σy = 340 Σ(x - )2 = 234 N = 4 Σ(y - )2 = 1974 SSR = 104 ​ The coefficient of correlation is

If the coefficient of determination is a positive value, then the coefficient of correlation

Correlation analysis is used to determine

If the coefficient of correlation is a negative value, then the coefficient of determination

In simple linear regression, r2 is the​

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

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 Sb1 = .2683 The t statistic for testing the significance of the slope is

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 Sb1 = .2683 The F statistic computed from the above data is

In simple linear regression, r is the

In regression analysis, the variable that is being predicted is the

If the coefficient of determination is equal to 1, then the coefficient of correlation

The following information regarding a dependent variable y and an independent variable x is provided: ​ The total sum of squares (SST) is

In regression analysis, if the dependent variable is measured in dollars, the independent variable

In a regression analysis, if SSE = 200 and SSR = 400, then the coefficient of determination is

SSE can never be

The following information regarding a dependent variable y and an independent variable x is provided: ​ The y-intercept is

In the following estimated regression equation = b0 + b1x,

The following information regarding a dependent variable y and an independent variable x is provided: ​ The mean square error (MSE) is

It is not possible for the coefficient of determination to be

Data and Statistics

Descriptive Statistics: Tabular and Graphical Displays

Descriptive Statistics: Numerical Measures

Introduction to Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling and Sampling Distributions

Interval Estimation

Hypothesis Tests

Inference About Means and Proportions With Two Populations

Inferences About Population Variances

Comparing Multiple Proportions, Tests of Independence and Goodness of Fit

Experimental Design and Analysis of Variance

Multiple Regression

Regression Analysis: Model Building

Time Series Analysis and Forecasting

Nonparametric Methods

Decision Analysis

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Statistical Methods for Quality Control

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The following information regarding a dependent variable y and an independent variable x is provided: Σx = 90 Σ(y - )(x - ) = -156 Σy = 340 Σ(x - )² = 234 N = 4 Σ(y - )² = 1974 SSR = 104 The coefficient of correlation is

In simple linear regression, r² is the

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

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 Sb₁ = .2683 The t statistic for testing the significance of the slope is

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 Sb₁ = .2683 The F statistic computed from the above data is

The following information regarding a dependent variable y and an independent variable x is provided: The total sum of squares (SST) is

The following information regarding a dependent variable y and an independent variable x is provided: The y-intercept is

In the following estimated regression equation = b₀ + b₁x,

The following information regarding a dependent variable y and an independent variable x is provided: The mean square error (MSE) is