Question 1

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 2

A simple regression analysis with 20 observations would yield ________ degrees of freedom error and _________ degrees of freedom total.

Accepted Answer

A) 1,20 
B) 18,19 
C) 19,20 
D) 1,19 
E) 18,20 
A) 1,20 
B) 18,19 
C) 19,20 
D) 1,19 
E) 18,20

Question 3

An experiment was performed on a certain metal to determine if the strength is a function of heating time.The 95 percent confidence interval for the average strength of a metal sheet when the average heating time is 4 minutes is from 4.325 to 5.675.Therefore,we are confident at α = .05 that the average strength of this metal heated for four minutes is between 4.325 and 5.675 pounds per square inch.Do you agree or disagree with this statement?

Accepted Answer

The answer of An experiment was performed on a certain...

Question 4

Consider the following partial computer output from a simple linear regression analysis.

Accepted Answer

\[\begin{array} { l l l r r } 
\text { V

Question 5

An experiment was performed on a certain metal to determine if the strength is a function of heating time.Results based on 10 metal sheets are given below.Use the simple linear regression model.

Accepted Answer

\[\begin{array} { l } 
\sum X = 30 \\

Question 6

A data set with 7 observations yielded the following.Use the simple linear regression model.

Accepted Answer

\[\begin{array} { l } 
\sum X = 21.57 \

Question 7

An experiment was performed on a certain metal to determine if the strength is a function of heating time.Results based on 10 metal sheets are given below.

Accepted Answer

\[\begin{array} { l } 
\sum X = 30 \\

Question 8

A local tire dealer wants to predict the number of tires sold each month.He believes that the number of tires sold is a linear function of the amount of money invested in advertising.He randomly selects 6 months of data consisting of tire sales (in thousands of tires)and advertising expenditures (in thousands of dollars).Based on the data set with 6 observations,the simple linear regression model yielded the following results.

Accepted Answer

\[\begin{array} { l } 
\sum X = 24 \\

Question 9

In simple regression analysis,if the correlation coefficient is a positive value,then:

Accepted Answer

A) The Y intercept must also be a positive value. 
B) The coefficient of determination can be either positive or negative,depending on the value of the slope. 
C) The least squares regression equation could either have a positive or a negative slope. 
D) The slope of the regression line must also be positive. 
E) The standard error of estimate can have either a positive or a negative valuE. 
A) The Y intercept must also be a positive value. 
B) The coefficient of determination can be either positive or negative,depending on the value of the slope. 
C) The least squares regression equation could either have a positive or a negative slope. 
D) The slope of the regression line must also be positive. 
E) The standard error of estimate can have either a positive or a negative valuE.

Question 10

Consider the following partial computer output from a simple linear regression analysis.

Accepted Answer

\[\begin{array} { l l l c c } 
\text { V

Question 11

Consider the following partial computer output from a simple linear regression analysis.

Accepted Answer

\[\begin{array} { l l l l l } 
\text { P

Question 12

Regression Analysis
  
The local grocery store wants to predict its daily sales in dollars.The manager believes that the amount of newspaper advertising significantly affects the store's 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 is the value of the simple coefficient of determination?

Accepted Answer

.762
Feedback:Read

Question 13

An experiment was performed on a certain metal to determine if the strength is a function of heating time.Results based on 10 metal sheets are given below.Use the simple linear regression model.

Accepted Answer

\[\begin{array} { l } 
\sum X = 30 \\

Question 14

The _____________ is the range of the previously observed values of x.

Accepted Answer

A) Population region 
B) Experimental region 
C) Slope 
D) Coefficient of determination 
A) Population region 
B) Experimental region 
C) Slope 
D) Coefficient of determination

Question 15

For the same value X (independent variable),the confidence interval for the average value of Y (dependent variable)is __________________ the prediction interval for the individual value of Y.

Accepted Answer

A) Larger than 
B) Smaller than 
C) The same as 
D) Sometimes larger than,sometimes smaller than 
A) Larger than 
B) Smaller than 
C) The same as 
D) Sometimes larger than,sometimes smaller than

Question 16

The correlation coefficient may assume any value between

Accepted Answer

A) 0 and 1 
B)  $- \infty$
And
$\infty$ 
C) 0 and 8 
D) -1,and 1 
E) -1,and 0 
A) 0 and 1 
B)  $- \infty$
And
$\infty$ 
C) 0 and 8 
D) -1,and 1 
E) -1,and 0

Question 17

A local tire dealer wants to predict the number of tires sold each month.He believes that the number of tires sold is a linear function of the amount of money invested in advertising.He randomly selects 6 months of data consisting of tire sales (in thousands of tires)and advertising expenditures (in thousands of dollars).Based on the data set with 6 observations,the simple linear regression model yielded the following results.

Accepted Answer

\[\begin{array} { l } 
\sum X = 24 \\

Question 18

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 19

If r = -1,then we can conclude that there is a perfect relationship between X and Y.

Accepted Answer

A) True 
 B)False

Question 20

A local tire dealer wants to predict the number of tires sold each month.He believes that the number of tires sold is a linear function of the amount of money invested in advertising.He randomly selects 6 months of data consisting of monthly tire sales (in thousands of tires)and monthly advertising expenditures (in thousands of dollars).Residuals are calculated for all of the randomly selected six months and ordered from smallest to largest.Determine the normal score for the smallest residual.

Accepted Answer

z₍₁₎ = -1.25 Feedback: \[\begin{a

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

A simple regression analysis with 20 observations would yield degrees of freedom error and _ degrees of freedom total.

Consider the following partial computer output from a simple linear regression analysis.

An experiment was performed on a certain metal to determine if the strength is a function of heating time.Results based on 10 metal sheets are given below.Use the simple linear regression model.

A data set with 7 observations yielded the following.Use the simple linear regression model.

An experiment was performed on a certain metal to determine if the strength is a function of heating time.Results based on 10 metal sheets are given below.

In simple regression analysis,if the correlation coefficient is a positive value,then:

Consider the following partial computer output from a simple linear regression analysis.

Consider the following partial computer output from a simple linear regression analysis.

An experiment was performed on a certain metal to determine if the strength is a function of heating time.Results based on 10 metal sheets are given below.Use the simple linear regression model.

The _____________ is the range of the previously observed values of x.

For the same value X (independent variable),the confidence interval for the average value of Y (dependent variable)is __________________ the prediction interval for the individual value of Y.

The correlation coefficient may assume any value between

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.

If r = -1,then we can conclude that there is a perfect relationship between X and Y.

Statistical Inferences for Population Variances

Experimental Design and Analysis of Variance

Chi-Square Tests

Multiple Regression and Model Building

Time Series Forecasting and Index Numbers

Process Improvement Using Control Charts

Nonparametric Methods

Decision Theory

Filters

Exam 14: Simple Linear Regression Analysis

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

A simple regression analysis with 20 observations would yield ________ degrees of freedom error and _________ degrees of freedom total.

Consider the following partial computer output from a simple linear regression analysis.

An experiment was performed on a certain metal to determine if the strength is a function of heating time.Results based on 10 metal sheets are given below.Use the simple linear regression model.

A data set with 7 observations yielded the following.Use the simple linear regression model.

An experiment was performed on a certain metal to determine if the strength is a function of heating time.Results based on 10 metal sheets are given below.

In simple regression analysis,if the correlation coefficient is a positive value,then:

Consider the following partial computer output from a simple linear regression analysis.

Consider the following partial computer output from a simple linear regression analysis.

An experiment was performed on a certain metal to determine if the strength is a function of heating time.Results based on 10 metal sheets are given below.Use the simple linear regression model.

The _____________ is the range of the previously observed values of x.

For the same value X (independent variable),the confidence interval for the average value of Y (dependent variable)is __________________ the prediction interval for the individual value of Y.

The correlation coefficient may assume any value between

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.

If r = -1,then we can conclude that there is a perfect relationship between X and Y.

Statistical Inferences for Population Variances

Experimental Design and Analysis of Variance

Chi-Square Tests

Multiple Regression and Model Building

Time Series Forecasting and Index Numbers

Process Improvement Using Control Charts

Nonparametric Methods

Decision Theory

Filters

A simple regression analysis with 20 observations would yield degrees of freedom error and _ degrees of freedom total.

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.