Question 1

In a regression analysis, the error term $\varepsilon$ is a random variable with a mean or expected value of

Accepted Answer

A) zero 
B) one 
C) any positive value 
D) any value 
A) zero 
B) one 
C) any positive value 
D) any value

Question 2

In a regression analysis the standard error is determined to be 4. In this situation the MSE

Accepted Answer

A) is 2 
B) is 16 
C) depends on the sample size 
D) depends on the degrees of freedom 
A) is 2 
B) is 16 
C) depends on the sample size 
D) depends on the degrees of freedom

Question 3

Exhibit 12-8
The following information regarding a dependent variable Y and an independent variable X is provided
  
-Refer to Exhibit 12-8. 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 4

In a regression and correlation analysis if r2 = 1, then

Accepted Answer

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 
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 5

Given below are five 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 $\alpha$ = 0.05.
d.Compute the coefficient of determination.
e.
Compute the coefficient of correlation.

Accepted Answer

a.@#IMG-DLM& = 8.3 - 0.15x
b.t = -15; p-value (act

Question 6

Exhibit 12-6
For the following data the value of SSE = 0.4130.
  
-Refer to Exhibit 12-6. The y intercept is

Accepted Answer

A) -1.5 
B) 24 
C) 0.50 
D) -0.707 
A) -1.5 
B) 24 
C) 0.50 
D) -0.707

Question 7

The model developed from sample data that has the form of   is known as

Accepted Answer

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

Question 8

Exhibit 12-10
The following information regarding a dependent variable Y and an independent variable X is provided.  
-Refer to Exhibit 12-10. The Y intercept is

Accepted Answer

A) -1 
B) 1.0 
C) 11 
D) 0.0 
A) -1 
B) 1.0 
C) 11 
D) 0.0

Question 9

Exhibit 12-5
The following information regarding a dependent variable (Y) and an independent variable (X) is provided.  
-Refer to Exhibit 12-5. The least squares estimate of the slope is

Accepted Answer

A) 1 
B) -1 
C) 0 
D) 3 
A) 1 
B) -1 
C) 0 
D) 3

Question 10

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 any units 
D) cannot be in dollars 
A) must also be in dollars 
B) must be in some units of currency 
C) can be any units 
D) cannot be in dollars

Question 11

Exhibit 12-10
The following information regarding a dependent variable Y and an independent variable X is provided.  
-Refer to Exhibit 12-10. The slope of the regression function is

Accepted Answer

A) -1 
B) 1.0 
C) 11 
D) 0.0 
A) -1 
B) 1.0 
C) 11 
D) 0.0

Question 12

In regression analysis, the unbiased estimate of the variance is

Accepted Answer

A) coefficient of correlation 
B) coefficient of determination 
C) mean square error 
D) slope of the regression equation 
A) coefficient of correlation 
B) coefficient of determination 
C) mean square error 
D) slope of the regression equation

Question 13

In a regression analysis if SST = 4500 and SSE = 1575, then the coefficient of determination is

Accepted Answer

A) 0.35 
B) 0.65 
C) 2.85 
D) 0.45 
A) 0.35 
B) 0.65 
C) 2.85 
D) 0.45

Question 14

Larger values of r2 imply that the observations are more closely grouped about the

Accepted Answer

A) average value of the independent variables 
B) average value of the dependent variable 
C) least squares line 
D) origin 
A) average value of the independent variables 
B) average value of the dependent variable 
C) least squares line 
D) origin

Question 15

The following data show the results of an aptitude test (Y) and the grade point average of 10 students.
   
a.Develop a least squares estimated regression line.
b.Compute the coefficient of determination and comment on the strength of the regression relationship.
c.Is the slope significant? Use a t test and let $\alpha$ = 0.05.
d.At 95% confidence, test to determine if the model is significant (i.e., perform an F test).

Accepted Answer

a.@#IMG-DLM&= 8.171 + 9.4564X
b.0.83; there is a f

Question 16

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 $\alpha$ = 0.05.
d.Compute the coefficient of determination.

Accepted Answer

a.@#IMG-DLM&= 13.75 -1.125X
b.t = -5.196; p-value

Question 17

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

Accepted Answer

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 
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 18

In a regression analysis, the variable that is being predicted

Accepted Answer

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 
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 19

Exhibit 12-4
Regression analysis was applied between sales data (Y in $1,000s) and advertising data (x in $100s) and the following information was obtained.
   = 12 + 1.8 x
n = 17
SSR = 225
SSE = 75
SS1U1B1bS1U1B0S1U1B11S1U1B0 = 0.2683
-Refer to Exhibit 12-4. 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 20

Exhibit 12-9
A regression and correlation analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x).
  
-Refer to Exhibit 12-9. The sum of squares due to regression (SSR) is

Accepted Answer

A) 1434 
B) 505.98 
C) 50.598 
D) 928.02 
A) 1434 
B) 505.98 
C) 50.598 
D) 928.02

In a regression analysis, the error term $\varepsilon$ is a random variable with a mean or expected value of

In a regression analysis the standard error is determined to be 4. In this situation the MSE

Exhibit 12-8 The following information regarding a dependent variable Y and an independent variable X is provided -Refer to Exhibit 12-8. The total sum of squares (SST) is

In a regression and correlation analysis if r² = 1, then

Exhibit 12-6 For the following data the value of SSE = 0.4130. -Refer to Exhibit 12-6. The y intercept is

The model developed from sample data that has the form of is known as

Exhibit 12-10 The following information regarding a dependent variable Y and an independent variable X is provided. -Refer to Exhibit 12-10. The Y intercept is

Exhibit 12-5 The following information regarding a dependent variable (Y) and an independent variable (X) is provided. -Refer to Exhibit 12-5. The least squares estimate of the slope is

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

Exhibit 12-10 The following information regarding a dependent variable Y and an independent variable X is provided. -Refer to Exhibit 12-10. The slope of the regression function is

In regression analysis, the unbiased estimate of the variance is

In a regression analysis if SST = 4500 and SSE = 1575, then the coefficient of determination is

Larger values of r² imply that the observations are more closely grouped about the

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

In a regression analysis, the variable that is being predicted

Exhibit 12-4 Regression analysis was applied between sales data (Y in $1,000s) and advertising data (x in $100s) and the following information was obtained. = 12 + 1.8 x n = 17 SSR = 225 SSE = 75 S_b₁ = 0.2683 -Refer to Exhibit 12-4. The F statistic computed from the above data is

Exhibit 12-9 A regression and correlation analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x). -Refer to Exhibit 12-9. The sum of squares due to regression (SSR) is

Data and Statistics

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Introduction to Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling and Sampling Distributions

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Comparisons Involving Means, Experimental Design and Analysis of Variance

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Exam 12: Simple Linear Regression

In a regression analysis, the error term ε\varepsilonε is a random variable with a mean or expected value of

In a regression analysis the standard error is determined to be 4. In this situation the MSE

Exhibit 12-8 The following information regarding a dependent variable Y and an independent variable X is provided -Refer to Exhibit 12-8. The total sum of squares (SST) is

In a regression and correlation analysis if r2 = 1, then

Exhibit 12-6 For the following data the value of SSE = 0.4130. -Refer to Exhibit 12-6. The y intercept is

The model developed from sample data that has the form of is known as

Exhibit 12-10 The following information regarding a dependent variable Y and an independent variable X is provided. -Refer to Exhibit 12-10. The Y intercept is

Exhibit 12-5 The following information regarding a dependent variable (Y) and an independent variable (X) is provided. -Refer to Exhibit 12-5. The least squares estimate of the slope is

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

Exhibit 12-10 The following information regarding a dependent variable Y and an independent variable X is provided. -Refer to Exhibit 12-10. The slope of the regression function is

In regression analysis, the unbiased estimate of the variance is

In a regression analysis if SST = 4500 and SSE = 1575, then the coefficient of determination is

Larger values of r2 imply that the observations are more closely grouped about the

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

In a regression analysis, the variable that is being predicted

Exhibit 12-4 Regression analysis was applied between sales data (Y in $1,000s) and advertising data (x in $100s) and the following information was obtained. = 12 + 1.8 x n = 17 SSR = 225 SSE = 75 Sb1 = 0.2683 -Refer to Exhibit 12-4. The F statistic computed from the above data is

Exhibit 12-9 A regression and correlation analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x). -Refer to Exhibit 12-9. The sum of squares due to regression (SSR) is

Data and Statistics

Descriptive Statistics: Tabular and Graphical Presentations

Descriptive Statistics: Numerical Measures

Introduction to Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling and Sampling Distributions

Interval Estimation

Hypothesis Tests

Comparisons Involving Means, Experimental Design and Analysis of Variance

Comparisons Involving Proportions and a Test of Independence

Multiple Regression

Filters

In a regression analysis, the error term $\varepsilon$ is a random variable with a mean or expected value of

In a regression and correlation analysis if r² = 1, then

Larger values of r² imply that the observations are more closely grouped about the

Exhibit 12-4 Regression analysis was applied between sales data (Y in $1,000s) and advertising data (x in $100s) and the following information was obtained. = 12 + 1.8 x n = 17 SSR = 225 SSE = 75 S_b₁ = 0.2683 -Refer to Exhibit 12-4. The F statistic computed from the above data is