Question 1

Regression analysis is a statistical procedure for developing a mathematical equation that describes how

Accepted Answer

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 alternatives is correct. 
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 alternatives is correct. C

Question 2

Given below are four 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

= 2.864 + 0.636x b.p-value < .05; reject H_o c.p-value < .05; reject H_o d.0.955

Question 3

Exhibit 12-10
The following information regarding a dependent variable Y and an independent variable X is provided.  
-Refer to Exhibit 12-10. The point estimate of Y when X = -3 is

Accepted Answer

A) 11 
B) 14 
C) 8 
D) 0 
A) 11 
B) 14 
C) 8 
D) 0 B

Question 4

Exhibit 12-5
The following information regarding a dependent variable (Y) and an independent variable (X) is provided.  
-Refer to Exhibit 12-5. The coefficient of correlation is

Accepted Answer

A) 0 
B) -1 
C) 0.5 
D) 1 
A) 0 
B) -1 
C) 0.5 
D) 1

Question 5

If only MSE is known, you can compute the

Accepted Answer

A) r square 
B) coefficient of determination 
C) standard error 
D) all of these alternatives are correct 
A) r square 
B) coefficient of determination 
C) standard error 
D) all of these alternatives are correct

Question 6

The interval estimate of the mean value of y for a given value of x is

Accepted Answer

A) prediction interval estimate 
B) confidence interval estimate 
C) average regression 
D) x versus y correlation interval 
A) prediction interval estimate 
B) confidence interval estimate 
C) average regression 
D) x versus y correlation interval

Question 7

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. To perform an F test, the p-value is

Accepted Answer

A) less than .01 
B) between .01 and .025 
C) between .025 and .05 
D) between .05 and 0.1 
A) less than .01 
B) between .01 and .025 
C) between .025 and .05 
D) between .05 and 0.1

Question 8

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 least squares estimate of b1 equals

Accepted Answer

A) 0.923 
B) 1.991 
C) -1.991 
D) -0.923 
A) 0.923 
B) 1.991 
C) -1.991 
D) -0.923

Question 9

Below you are given a partial computer output based on a sample of 21 observations, relating an independent variable (x) and a dependent variable (y).
     
a.Develop the estimated regression line.
b.At $\alpha$ = 0.05, test for the significance of the slope.
c.At $\alpha$= 0.05, perform an F test.
d.Determine the coefficient of determination.
e.
Determine the coefficient of correlation.

Accepted Answer

a.@#IMG-DLM& = 30.139 - 0.252X
b.t = -11.357; p-va

Question 10

The coefficient of correlation

Accepted Answer

A) is the square of the coefficient of determination 
B) is the square root of the coefficient of determination 
C) is the same as r-square 
D) can never be negative 
A) is the square of the coefficient of determination 
B) is the square root of the coefficient of determination 
C) is the same as r-square 
D) can never be negative

Question 11

Exhibit 12-5
The following information regarding a dependent variable (Y) and an independent variable (X) is provided.  
-Refer to Exhibit 12-5. The coefficient of determination is

Accepted Answer

A) 0 
B) -1 
C) 0.5 
D) 1 
A) 0 
B) -1 
C) 0.5 
D) 1

Question 12

Assume you have noted the following prices for paperback books and the number of pages that each book contains.
   
a.Develop a least-squares estimated regression line.
b.Compute the coefficient of determination and explain its meaning.
c.Compute the correlation coefficient between the price and the number of pages. Test to see if x and y are related. Use $\alpha$ = 0.10.

Accepted Answer

a.= 1.0416 + 0.0099x b.r ² =

Question 13

In regression analysis, the model in the form   is called

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 14

Exhibit 12-2
You are given the following information about y and x.
  
-Refer to Exhibit 12-2. The least squares estimate of b1 (slope) equals

Accepted Answer

A) 1 
B) -1 
C) 6 
D) 5 
A) 1 
B) -1 
C) 6 
D) 5

Question 15

Exhibit 12-7
You are given the following information about y and x.
  
-Refer to Exhibit 12-7. The sample correlation coefficient equals

Accepted Answer

A) 0.3162 
B) -0.3162 
C) 0.10 
D) -0.10 
A) 0.3162 
B) -0.3162 
C) 0.10 
D) -0.10

Question 16

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

Question 17

If the coefficient of correlation is 0.4, the percentage of variation in the dependent variable explained by the variation in the independent variable

Accepted Answer

A) is 40% 
B) is 16%. 
C) is 4% 
D) can be any positive value 
A) is 40% 
B) is 16%. 
C) is 4% 
D) can be any positive value

Question 18

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 is

Accepted Answer

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 
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 19

Exhibit 12-2
You are given the following information about y and x.
  
-Refer to Exhibit 12-2. The least squares estimate of b0 (intercept)equals

Accepted Answer

A) 1 
B) -1 
C) 6 
D) 5 
A) 1 
B) -1 
C) 6 
D) 5

Question 20

In regression analysis, which of the following is not a required assumption about the error term $\varepsilon$?

Accepted Answer

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. 
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.

Regression analysis is a statistical procedure for developing a mathematical equation that describes how

Exhibit 12-10 The following information regarding a dependent variable Y and an independent variable X is provided. -Refer to Exhibit 12-10. The point estimate of Y when X = -3 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 coefficient of correlation is

If only MSE is known, you can compute the

The interval estimate of the mean value of y for a given value of x is

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. To perform an F test, the p-value 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 least squares estimate of b₁ equals

The coefficient of correlation

Exhibit 12-5 The following information regarding a dependent variable (Y) and an independent variable (X) is provided. -Refer to Exhibit 12-5. The coefficient of determination is

In regression analysis, the model in the form is called

Exhibit 12-2 You are given the following information about y and x. -Refer to Exhibit 12-2. The least squares estimate of b₁ (slope) equals

Exhibit 12-7 You are given the following information about y and x. -Refer to Exhibit 12-7. The sample correlation coefficient equals

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

If the coefficient of correlation is 0.4, the percentage of variation in the dependent variable explained by the variation in the independent variable

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 is

Exhibit 12-2 You are given the following information about y and x. -Refer to Exhibit 12-2. The least squares estimate of b₀ (intercept)equals

In regression analysis, which of the following is not a required assumption about the error term $\varepsilon$ ?

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

Exam 12: Simple Linear Regression

Regression analysis is a statistical procedure for developing a mathematical equation that describes how

Exhibit 12-10 The following information regarding a dependent variable Y and an independent variable X is provided. -Refer to Exhibit 12-10. The point estimate of Y when X = -3 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 coefficient of correlation is

If only MSE is known, you can compute the

The interval estimate of the mean value of y for a given value of x is

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. To perform an F test, the p-value 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 least squares estimate of b1 equals

The coefficient of correlation

Exhibit 12-5 The following information regarding a dependent variable (Y) and an independent variable (X) is provided. -Refer to Exhibit 12-5. The coefficient of determination is

In regression analysis, the model in the form is called

Exhibit 12-2 You are given the following information about y and x. -Refer to Exhibit 12-2. The least squares estimate of b1 (slope) equals

Exhibit 12-7 You are given the following information about y and x. -Refer to Exhibit 12-7. The sample correlation coefficient equals

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

If the coefficient of correlation is 0.4, the percentage of variation in the dependent variable explained by the variation in the independent variable

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 is

Exhibit 12-2 You are given the following information about y and x. -Refer to Exhibit 12-2. The least squares estimate of b0 (intercept)equals

In regression analysis, which of the following is not a required assumption about the error term ε\varepsilonε ?

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

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. To perform an F test, the p-value 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 least squares estimate of b₁ equals

Exhibit 12-2 You are given the following information about y and x. -Refer to Exhibit 12-2. The least squares estimate of b₁ (slope) equals

Exhibit 12-2 You are given the following information about y and x. -Refer to Exhibit 12-2. The least squares estimate of b₀ (intercept)equals

In regression analysis, which of the following is not a required assumption about the error term $\varepsilon$ ?