Question 1

If the Durbin-Watson statistic is less than dL, then we conclude that

Accepted Answer

A)  there is significant positive autocorrelation. 
B)  there is significant negative autocorrelation. 
C)  there is significant autocorrelation, but we cannot identify whether it is positive or negative. 
D)  the test results are inconclusive. 
A)  there is significant positive autocorrelation. 
B)  there is significant negative autocorrelation. 
C)  there is significant autocorrelation, but we cannot identify whether it is positive or negative. 
D)  the test results are inconclusive.

Question 2

If successive values of the residuals are close together, then there is a ________ autocorrelation and the value of the Durbin-Watson statistic is ________.

Accepted Answer

A)  negative; large 
B)  positive; small 
C)  negative; small 
D)  positive; large 
A)  negative; large 
B)  positive; small 
C)  negative; small 
D)  positive; large

Question 3

The least squares regression line minimizes the sum of the

Accepted Answer

A)  differences between actual and predicted Y values. 
B)  absolute deviations between actual and predicted Y values. 
C)  absolute deviations between actual and predicted X values. 
D)  squared differences between actual and predicted Y values. 
E)  squared differences between actual and predicted X values. 
A)  differences between actual and predicted Y values. 
B)  absolute deviations between actual and predicted Y values. 
C)  absolute deviations between actual and predicted X values. 
D)  squared differences between actual and predicted Y values. 
E)  squared differences between actual and predicted X values.

Question 4

When there is positive autocorrelation, over time, negative error terms are followed by positive error terms and positive error terms are followed by negative error terms.

Accepted Answer

A) True 
 B)False

Question 5

A ________ measures the strength of the relationship between a dependent variable (Y) and an independent variable (X).

Accepted Answer

A)  coefficient of determination 
B)  correlation coefficient 
C)  slope 
D)  standard error 
A)  coefficient of determination 
B)  correlation coefficient 
C)  slope 
D)  standard error

Question 6

In a simple linear regression model, the slope term is the change in the mean value of y associated with ________ in x.

Accepted Answer

A)  a corresponding increase 
B)  a variable change 
C)  no change 
D)  a one-unit increase 
A)  a corresponding increase 
B)  a variable change 
C)  no change 
D)  a one-unit increase

Question 7

A simple linear regression model is an equation that describes the straight-line relationship between a dependent variable and an independent variable.

Accepted Answer

A) True 
 B)False

Question 8

Consider the following partial computer output from a simple linear regression analysis.
   S = .4862R-Sq = ________
Analysis of Variance
   What is the estimated y-intercept?

Accepted Answer

The answer of Consider the following partial computer output from...

Question 9

An experiment was performed on a certain metal to determine if the strength is a function of heating time. Partial results based on a sample of 10 metal sheets are given below. The simple linear regression equation is ŷ = 1 + 1X. The time is in minutes, the strength is measured in pounds per square inch, MSE = .5, Σx = 30, and Σx2 = 104. Determine the 95 percent confidence interval for the average strength of a metal sheet when the average heating time is 2.5 minutes.

Accepted Answer

[2.94, 4.06]
ŷ = 1 + 1(2.5) =

Question 10

When the assumption of ________ residuals (error terms) is violated, the Durbin-Watson statistic is used to test to determine if there is significant ________ among the residuals.

Accepted Answer

A)  normality; probability 
B)  independent; probability 
C)  independent; autocorrelation 
D)  normality; autocorrelation 
A)  normality; probability 
B)  independent; probability 
C)  independent; autocorrelation 
D)  normality; autocorrelation

Question 11

The range for r2 is between 0 and 1, and the range for r is between ________.

Accepted Answer

A)  0 and 1 
B)  −1 and 1 
C)  −1 and 0 
D)  There is no limit for r. 
A)  0 and 1 
B)  −1 and 1 
C)  −1 and 0 
D)  There is no limit for r.

Question 12

A data set with 7 observations yielded the following. Use the simple linear regression model.
∑X = 21.57
∑X2 = 68.31
∑Y = 188.9
∑Y2 = 5,140.23
∑XY = 590.83
SSE = 1.117
Determine the 95 percent confidence interval for the average value of Y when x = 3.25.

Accepted Answer

[27.30, 28.26] b₁ = @#IMG-DLM& = @#IMG-DLM& = @#IMG-DLM& = 4.745 ŷ = 12

Question 13

The estimated simple linear regression equation minimizes the sum of the squared deviations between each value of Y and the line.

Accepted Answer

A) True 
 B)False

Question 14

The simple linear regression (least squares method) minimizes

Accepted Answer

A)  the explained variation. 
B)  SSyy. 
C)  total variation. 
D)  SSxx. 
E)  SSE. 
A)  the explained variation. 
B)  SSyy. 
C)  total variation. 
D)  SSxx. 
E)  SSE.

Question 15

Regression Analysis
   ANOVA
   Regression output
   A local grocery store wants to predict its daily sales in dollars. The manager believes that the amount of newspaper advertising significantly affects sales. He randomly selects 7 days of data consisting of daily grocery store sales (in thousands of dollars) and advertising expenditures (in thousands of dollars). The Excel/MegaStat output given above summarizes the results of the regression model.
What are the limits of the 95 percent confidence interval for the population slope?

Accepted Answer

[2.377, 10.963] Using t._05/2,_df = 5,

Question 16

The simple coefficient of determination is the proportion of total variation explained by the regression line.

Accepted Answer

A) True 
 B)False

Question 17

Regression Analysis
   ANOVA
   Regression output
   A local grocery store wants to predict its daily sales in dollars. The manager believes that the amount of newspaper advertising significantly affects sales. He randomly selects 7 days of data consisting of daily grocery store sales (in thousands of dollars) and advertising expenditures (in thousands of dollars). The Excel/MegaStat output given above summarizes the results of the regression model.
If the manager decides to spend $3,000 on advertising, based on the simple linear regression results given above, what are the estimated sales?

Accepted Answer

$83,333
Estimated sa

Question 18

In a simple linear regression model, the coefficient of determination not only indicates the strength of the relationship between the independent and dependent variables, but also shows whether the relationship is positive or negative.

Accepted Answer

A) True 
 B)False

Question 19

The following results were obtained as part of a simple regression analysis. r2 = .9162
F statistic from the F table = 3.59
Calculated value of F from the ANOVA table = 81.87
Α = .05
P-value = .000
The null hypothesis of no linear relationship between the dependent variable and the independent variable

Accepted Answer

A)  is rejected. 
B)  cannot be tested with the given information. 
C)  is not rejected. 
D)  is not an appropriate null hypothesis for this situation. 
A)  is rejected. 
B)  cannot be tested with the given information. 
C)  is not rejected. 
D)  is not an appropriate null hypothesis for this situation.

Question 20

Consider the following partial computer output from a simple linear regression analysis.
   S = .4862R-Sq = ________
Analysis of Variance
   What is the coefficient of determination?

Accepted Answer

r² = .7286 Explained variance =

If the Durbin-Watson statistic is less than d_L, then we conclude that

If successive values of the residuals are close together, then there is a autocorrelation and the value of the Durbin-Watson statistic is .

The least squares regression line minimizes the sum of the

When there is positive autocorrelation, over time, negative error terms are followed by positive error terms and positive error terms are followed by negative error terms.

A ________ measures the strength of the relationship between a dependent variable (Y) and an independent variable (X).

In a simple linear regression model, the slope term is the change in the mean value of y associated with ________ in x.

A simple linear regression model is an equation that describes the straight-line relationship between a dependent variable and an independent variable.

Consider the following partial computer output from a simple linear regression analysis. S = .4862R-Sq = ________ Analysis of Variance What is the estimated y-intercept?

When the assumption of residuals (error terms) is violated, the Durbin-Watson statistic is used to test to determine if there is significant among the residuals.

The range for r² is between 0 and 1, and the range for r is between ________.

A data set with 7 observations yielded the following. Use the simple linear regression model. ∑X = 21.57 ∑X² = 68.31 ∑Y = 188.9 ∑Y² = 5,140.23 ∑XY = 590.83 SSE = 1.117 Determine the 95 percent confidence interval for the average value of Y when x = 3.25.

The estimated simple linear regression equation minimizes the sum of the squared deviations between each value of Y and the line.

The simple linear regression (least squares method) minimizes

The simple coefficient of determination is the proportion of total variation explained by the regression line.

In a simple linear regression model, the coefficient of determination not only indicates the strength of the relationship between the independent and dependent variables, but also shows whether the relationship is positive or negative.

Consider the following partial computer output from a simple linear regression analysis. S = .4862R-Sq = ________ Analysis of Variance What is the coefficient of determination?

An Introduction to Business Statistics and Analytics

Descriptive Statistics and Analytics: Tabular and Graphical Methods

Descriptive Statistics and Analytics: Numerical Methods

Probability and Probability Models

Predictive Analytics I: Trees, K-Nearest Neighbors, Naive Bayes,

Discrete Random Variables

Continuous Random Variables

Sampling Distributions

Confidence Intervals

Hypothesis Testing

Statistical Inferences Based on Two Samples

Experimental Design and Analysis of Variance

Chi-Square Tests

Multiple Regression and Model Building

Predictive Analytics Ii: Logistic Regression, Discriminate Analysis,

Time Series Forecasting and Index Numbers

Nonparametric Methods

Decision Theory

Filters

Exam 14: Simple Linear Regression Analysis

If the Durbin-Watson statistic is less than dL, then we conclude that

If successive values of the residuals are close together, then there is a ________ autocorrelation and the value of the Durbin-Watson statistic is ________.

The least squares regression line minimizes the sum of the

When there is positive autocorrelation, over time, negative error terms are followed by positive error terms and positive error terms are followed by negative error terms.

A ________ measures the strength of the relationship between a dependent variable (Y) and an independent variable (X).

In a simple linear regression model, the slope term is the change in the mean value of y associated with ________ in x.

A simple linear regression model is an equation that describes the straight-line relationship between a dependent variable and an independent variable.

Consider the following partial computer output from a simple linear regression analysis. S = .4862R-Sq = ________ Analysis of Variance What is the estimated y-intercept?

When the assumption of ________ residuals (error terms) is violated, the Durbin-Watson statistic is used to test to determine if there is significant ________ among the residuals.

The range for r2 is between 0 and 1, and the range for r is between ________.

A data set with 7 observations yielded the following. Use the simple linear regression model. ∑X = 21.57 ∑X2 = 68.31 ∑Y = 188.9 ∑Y2 = 5,140.23 ∑XY = 590.83 SSE = 1.117 Determine the 95 percent confidence interval for the average value of Y when x = 3.25.

The estimated simple linear regression equation minimizes the sum of the squared deviations between each value of Y and the line.

The simple linear regression (least squares method) minimizes

The simple coefficient of determination is the proportion of total variation explained by the regression line.

In a simple linear regression model, the coefficient of determination not only indicates the strength of the relationship between the independent and dependent variables, but also shows whether the relationship is positive or negative.

Consider the following partial computer output from a simple linear regression analysis. S = .4862R-Sq = ________ Analysis of Variance What is the coefficient of determination?

An Introduction to Business Statistics and Analytics

Descriptive Statistics and Analytics: Tabular and Graphical Methods

Descriptive Statistics and Analytics: Numerical Methods

Probability and Probability Models

Predictive Analytics I: Trees, K-Nearest Neighbors, Naive Bayes,

Discrete Random Variables

Continuous Random Variables

Sampling Distributions

Confidence Intervals

Hypothesis Testing

Statistical Inferences Based on Two Samples

Experimental Design and Analysis of Variance

Chi-Square Tests

Multiple Regression and Model Building

Predictive Analytics Ii: Logistic Regression, Discriminate Analysis,

Time Series Forecasting and Index Numbers

Nonparametric Methods

Decision Theory

Filters

If the Durbin-Watson statistic is less than d_L, then we conclude that

If successive values of the residuals are close together, then there is a autocorrelation and the value of the Durbin-Watson statistic is .

When the assumption of residuals (error terms) is violated, the Durbin-Watson statistic is used to test to determine if there is significant among the residuals.

The range for r² is between 0 and 1, and the range for r is between ________.

A data set with 7 observations yielded the following. Use the simple linear regression model. ∑X = 21.57 ∑X² = 68.31 ∑Y = 188.9 ∑Y² = 5,140.23 ∑XY = 590.83 SSE = 1.117 Determine the 95 percent confidence interval for the average value of Y when x = 3.25.