Question 1

Consider the following partial computer output from a simple linear regression analysis.   What is the estimated y-intercept?

Accepted Answer

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

Question 2

The coefficient of determination measures the _____________ explained by the simple linear regression model.

Accepted Answer

A)  correlation 
B)  proportion of variation 
C)  standard error 
D)  mean square error 
A)  correlation 
B)  proportion of variation 
C)  standard error 
D)  mean square error

Question 3

An experiment was performed on a certain metal to determine if its 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 
 = 1 + 1X .Time is in minutes,strength is measured in pounds per square inch,MSE  
 = 0.5,= 30,and
 = 104.The distance value has been found to be equal to 0.17143.Determine the 95 percent prediction interval for the strength of a metal sheet when the average heating time is 4 minutes.

Accepted Answer

[3.235,6.765] 
@#IMG-DLM&= 1 + 1(4)= 5
D

Question 4

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.   Determine the values of SSE and SST.

Accepted Answer

SSE = 16,S

Question 5

Consider the following partial computer output from a simple linear regression analysis.   Test to determine if there is a significant correlation between x and y.Use H0: ρ = 0 versus Ha: ρ ≠ 0 with α = .01.Show the test statistic used in the decision.

Accepted Answer

t = −5.908 < −2.977.Reject H₀;there is a

Question 6

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.   Find the rejection point for the t statistic at α = .05 and test H0: β1 = 0 vs.Ha: β1 ≠ 0.

Accepted Answer

t = 2.645

Question 7

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

Question 8

In a simple regression analysis for a given data set,if the null hypothesis β = 0 is rejected,then the null hypothesis ρ = 0 is also rejected.This statement is ___________ true.

Accepted Answer

A)  always 
B)  never 
C)  sometimes 
A)  always 
B)  never 
C)  sometimes

Question 9

The strength of the relationship between two quantitative variables can be measured by

Accepted Answer

A)  the slope of a simple linear regression equation. 
B)  the y-intercept of the simple linear regression equation. 
C)  the coefficient of correlation. 
D)  the coefficient of determination. 
E)  both the coefficient of correlation and the coefficient of determination. 
A)  the slope of a simple linear regression equation. 
B)  the y-intercept of the simple linear regression equation. 
C)  the coefficient of correlation. 
D)  the coefficient of determination. 
E)  both the coefficient of correlation and the coefficient of determination.

Question 10

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 equation of the least squares line is ŷ = 3 + 1x.   MSE = 4
Using the sums of the squares given above,determine the 90 percent prediction interval for tire sales in a month when the advertising expenditure is $5,000.

Accepted Answer

[3.32,12.68]
Ŷ = 3 + 1(5)= 8
S

Question 11

The ___________ of the simple linear regression model is the value of y when the mean value of x is zero.

Accepted Answer

A)  y-intercept 
B)  slope 
C)  independent variable 
D)  response variable 
A)  y-intercept 
B)  slope 
C)  independent variable 
D)  response variable

Question 12

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 third residual in the ordered array.

Accepted Answer

The answer of A local tire dealer wants to predict...

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.   Determine SSE and SS(Total).

Accepted Answer

SSE = 4,SS

Question 14

In simple linear regression analysis,if the error terms exhibit a positive or negative autocorrelation over time,then the assumption of constant variance is violated.

Accepted Answer

A) True 
 B)False

Question 15

The Durbin-Watson test statistic ranges from

Accepted Answer

A)  −4 to 4. 
B)  0 to 4. 
C)  0 to 3. 
D)  −1 to 1. 
E)  0 to 1. 
A)  −4 to 4. 
B)  0 to 4. 
C)  0 to 3. 
D)  −1 to 1. 
E)  0 to 1.

Question 16

An experiment was performed on a certain metal to determine if the strength is a function of heating time.The 95 percent prediction interval for the strength of a metal sheet when the average heating time is 4 minutes is from 3.235 to 6.765.We are 95 percent confident that an individual sheet of metal heated for four minutes will have strength of at least 4 pounds per square inch.Do you agree with this statement?

Accepted Answer

No,I do not agree with this statement.
W

Question 17

The least squares point estimates of the simple linear regression model minimize the ____________.

Accepted Answer

A)  SS error 
B)  total variance 
C)  MS error 
D)  explained variance 
A)  SS error 
B)  total variance 
C)  MS error 
D)  explained variance

Question 18

In simple regression analysis,the quantity that gives the amount by which Y (dependent variable)changes for a unit change in X (independent variable)is called the

Accepted Answer

A)  coefficient of determination. 
B)  slope of the regression line. 
C)  y-intercept of the regression line. 
D)  correlation coefficient. 
E)  standard error. 
A)  coefficient of determination. 
B)  slope of the regression line. 
C)  y-intercept of the regression line. 
D)  correlation coefficient. 
E)  standard error.

Question 19

The following results were obtained from a simple regression analysis.Ŷ = 37.2895 − (1.2024)X
r2 = .6744sb = .2934
What is the proportion of the variation explained by the simple linear regression model?

Accepted Answer

.6774
The coefficien

Question 20

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.

Consider the following partial computer output from a simple linear regression analysis. What is the estimated y-intercept?

The coefficient of determination measures the _____________ explained by the simple linear regression model.

Consider the following partial computer output from a simple linear regression analysis. Test to determine if there is a significant correlation between x and y.Use H₀: ρ = 0 versus H_a: ρ ≠ 0 with α = .01.Show the test statistic used in the decision.

In a simple regression analysis for a given data set,if the null hypothesis β = 0 is rejected,then the null hypothesis ρ = 0 is also rejected.This statement is ___________ true.

The strength of the relationship between two quantitative variables can be measured by

The ___________ of the simple linear regression model is the value of y when the mean value of x is zero.

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. Determine SSE and SS(Total).

In simple linear regression analysis,if the error terms exhibit a positive or negative autocorrelation over time,then the assumption of constant variance is violated.

The Durbin-Watson test statistic ranges from

The least squares point estimates of the simple linear regression model minimize the ____________.

In simple regression analysis,the quantity that gives the amount by which Y (dependent variable)changes for a unit change in X (independent variable)is called the

The following results were obtained from a simple regression analysis.Ŷ = 37.2895 − (1.2024)X r² = .6744s_b = .2934 What is the proportion of the variation explained by the simple linear regression model?

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

An Introduction to Business Statistics

Descriptive Statistics: Tabular and Graphical Methods

Descriptive Statistics: Numerical Methods

Probability

Discrete Random Variables

Continuous Random Variables

Sampling and Sampling Distributions

Confidence Intervals

Hypothesis Testing

Statistical Inferences for Means and Proportions

Statistical Inferences for Population Variances

Experimental Design and Analysis of Variance

Simple Linear Regression Analysis

Multiple Regression and Model Building

Time Series Forecasting and Index Numbers

Nonparametric Methods

Decision Theory

Filters

Exam 13: Chi-Square Tests

Consider the following partial computer output from a simple linear regression analysis. What is the estimated y-intercept?

The coefficient of determination measures the _____________ explained by the simple linear regression model.

Consider the following partial computer output from a simple linear regression analysis. Test to determine if there is a significant correlation between x and y.Use H0: ρ = 0 versus Ha: ρ ≠ 0 with α = .01.Show the test statistic used in the decision.

In a simple regression analysis for a given data set,if the null hypothesis β = 0 is rejected,then the null hypothesis ρ = 0 is also rejected.This statement is ___________ true.

The strength of the relationship between two quantitative variables can be measured by

The ___________ of the simple linear regression model is the value of y when the mean value of x is zero.

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. Determine SSE and SS(Total).

In simple linear regression analysis,if the error terms exhibit a positive or negative autocorrelation over time,then the assumption of constant variance is violated.

The Durbin-Watson test statistic ranges from

The least squares point estimates of the simple linear regression model minimize the ____________.

In simple regression analysis,the quantity that gives the amount by which Y (dependent variable)changes for a unit change in X (independent variable)is called the

The following results were obtained from a simple regression analysis.Ŷ = 37.2895 − (1.2024)X r2 = .6744sb = .2934 What is the proportion of the variation explained by the simple linear regression model?

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

An Introduction to Business Statistics

Descriptive Statistics: Tabular and Graphical Methods

Descriptive Statistics: Numerical Methods

Probability

Discrete Random Variables

Continuous Random Variables

Sampling and Sampling Distributions

Confidence Intervals

Hypothesis Testing

Statistical Inferences for Means and Proportions

Statistical Inferences for Population Variances

Experimental Design and Analysis of Variance

Simple Linear Regression Analysis

Multiple Regression and Model Building

Time Series Forecasting and Index Numbers

Nonparametric Methods

Decision Theory

Filters

Consider the following partial computer output from a simple linear regression analysis. Test to determine if there is a significant correlation between x and y.Use H₀: ρ = 0 versus H_a: ρ ≠ 0 with α = .01.Show the test statistic used in the decision.

The following results were obtained from a simple regression analysis.Ŷ = 37.2895 − (1.2024)X r² = .6744s_b = .2934 What is the proportion of the variation explained by the simple linear regression model?

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