The following results were obtained from a simple regression analysis: = 37.2895 - (1.2024)X r2= .6744 sb = .2934 For each unit change in X (independent variable),the estimated change in Y (dependent variable)is equal to:

A) -1.2024 B) .6774 C) 37.2895 D) .2934 A) -1.2024 B) .6774 C) 37.2895 D) .2934

Exam 13: Simple Linear Regression Analysis

A data set with 7 observations yielded the following.Use the simple linear regression model. = 21.57 = 68.31 = 188.9 = 5,140.23 = 590.83 SSE = 1.06 Find the estimated slope.

(Multiple Choice)

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Question 41

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.

(Multiple Choice)

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Question 42

The correlation coefficient is the ratio of explained variation to total variation.

(True/False)

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Question 43

The slope of the simple linear regression equation represents the average change in the value of the dependent variable per unit change in the independent variable (X).

(True/False)

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Question 44

Which of the following is a violation of one of the major assumptions of the simple regression model?

(Multiple Choice)

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Question 45

If the points are tightly distributed around the regression line on a scatter diagram,then we can conclude that the changes in the value of the dependent variable _________ the independent variable (X).

(Multiple Choice)

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Question 46

A data set with 7 observations yielded the following.Use the simple linear regression model. = 21.57 = 68.31 = 188.9 = 5,140.23 = 590.83 SSE = 1.06 Determine the 95% confidence interval for the average value of Y when x = 3.25.

(Multiple Choice)

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Question 47

The following results were obtained from a simple regression analysis: = 37.2895 - (1.2024)X r²= .6744 s_b = .2934 For each unit change in X (independent variable),the estimated change in Y (dependent variable)is equal to:

(Multiple Choice)

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Question 48

When using simple linear regression,we would like to use confidence intervals for the _ and prediction intervals for the _ at a given value of x.

(Multiple Choice)

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Question 49

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. = 30 = 104 = 40 = 178 = 134 Determine SSE,SS (Total)

(Multiple Choice)

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Question 50

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

(Multiple Choice)

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Question 51

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. $A local tire dealer wants to predict the number of tires sold each month.He believes that the number of tires sold is a linear function of the amount of money invested in advertising.He randomly selects 6 months of data consisting of tire sales (in thousands of tires)and advertising expenditures (in thousands of dollars).Based on the data set with 6 observations,the simple linear regression model yielded the following results. = 24 = 124 = 42 = 338 = 196 Find the rejection point for the t statistic at \alpha = .05 and test H0: \beta 1 = 0 vs.Ha: \beta 1 \neq 0.$ = 24 $A local tire dealer wants to predict the number of tires sold each month.He believes that the number of tires sold is a linear function of the amount of money invested in advertising.He randomly selects 6 months of data consisting of tire sales (in thousands of tires)and advertising expenditures (in thousands of dollars).Based on the data set with 6 observations,the simple linear regression model yielded the following results. = 24 = 124 = 42 = 338 = 196 Find the rejection point for the t statistic at \alpha = .05 and test H0: \beta 1 = 0 vs.Ha: \beta 1 \neq 0.$ = 124 $A local tire dealer wants to predict the number of tires sold each month.He believes that the number of tires sold is a linear function of the amount of money invested in advertising.He randomly selects 6 months of data consisting of tire sales (in thousands of tires)and advertising expenditures (in thousands of dollars).Based on the data set with 6 observations,the simple linear regression model yielded the following results. = 24 = 124 = 42 = 338 = 196 Find the rejection point for the t statistic at \alpha = .05 and test H0: \beta 1 = 0 vs.Ha: \beta 1 \neq 0.$ = 42 $A local tire dealer wants to predict the number of tires sold each month.He believes that the number of tires sold is a linear function of the amount of money invested in advertising.He randomly selects 6 months of data consisting of tire sales (in thousands of tires)and advertising expenditures (in thousands of dollars).Based on the data set with 6 observations,the simple linear regression model yielded the following results. = 24 = 124 = 42 = 338 = 196 Find the rejection point for the t statistic at \alpha = .05 and test H0: \beta 1 = 0 vs.Ha: \beta 1 \neq 0.$ = 338 $A local tire dealer wants to predict the number of tires sold each month.He believes that the number of tires sold is a linear function of the amount of money invested in advertising.He randomly selects 6 months of data consisting of tire sales (in thousands of tires)and advertising expenditures (in thousands of dollars).Based on the data set with 6 observations,the simple linear regression model yielded the following results. = 24 = 124 = 42 = 338 = 196 Find the rejection point for the t statistic at \alpha = .05 and test H0: \beta 1 = 0 vs.Ha: \beta 1 \neq 0.$ = 196 Find the rejection point for the t statistic at $\alpha$ = .05 and test H₀: $\beta$ ₁ = 0 vs.H_a: $\beta$ ₁ $\neq$ 0.

(Multiple Choice)

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Question 52

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. = 24 = 124 = 42 = 338 = 196 Calculate the standard error.

(Multiple Choice)

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Question 53

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

(Multiple Choice)

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Question 54

An experiment was performed on a certain metal to determine if the strength is a function of heating time.The simple linear regression equation is = 1 + 1X.The time is in minutes and the strength is measured in pounds per square inch. Provide a managerial interpretation of the slope.

(Multiple Choice)

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Question 55

An experiment was performed on a certain metal to determine if the strength is a function of heating time.The sample size consists of ten metal sheets.Residuals are calculated for all ten metal sheets and ordered from smallest to largest. Determine the normal point for the second largest residual (ninth residual in the ordered array).

(Multiple Choice)

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Question 56

_____ is a statistical technique in which we use observed data to relate a dependent variable to one or more predictor (independent)variables.

(Multiple Choice)

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Question 57

Consider the following partial computer output from a simple linear regression analysis. S = 0.4862 R-Sq = ______ Analysis of Variance Calculate the MSE.

(Multiple Choice)

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Question 58

_____ distribution is used for testing the significance of the slope term.

(Multiple Choice)

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Question 59

_____ measures the strength of the linear relationship between the dependent and the independent variable.

(Multiple Choice)

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Question 60

Showing 41 - 60 of 148

A data set with 7 observations yielded the following.Use the simple linear regression model. = 21.57 = 68.31 = 188.9 = 5,140.23 = 590.83 SSE = 1.06 Find the estimated slope.

The correlation coefficient is the ratio of explained variation to total variation.

The slope of the simple linear regression equation represents the average change in the value of the dependent variable per unit change in the independent variable (X).

Which of the following is a violation of one of the major assumptions of the simple regression model?

If the points are tightly distributed around the regression line on a scatter diagram,then we can conclude that the changes in the value of the dependent variable _________ the independent variable (X).

A data set with 7 observations yielded the following.Use the simple linear regression model. = 21.57 = 68.31 = 188.9 = 5,140.23 = 590.83 SSE = 1.06 Determine the 95% confidence interval for the average value of Y when x = 3.25.

The following results were obtained from a simple regression analysis: = 37.2895 - (1.2024)X r²= .6744 s_b = .2934 For each unit change in X (independent variable),the estimated change in Y (dependent variable)is equal to:

When using simple linear regression,we would like to use confidence intervals for the _ and prediction intervals for the _ at a given value of x.

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. = 30 = 104 = 40 = 178 = 134 Determine SSE,SS (Total)

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

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

An experiment was performed on a certain metal to determine if the strength is a function of heating time.The simple linear regression equation is = 1 + 1X.The time is in minutes and the strength is measured in pounds per square inch. Provide a managerial interpretation of the slope.

_____ is a statistical technique in which we use observed data to relate a dependent variable to one or more predictor (independent)variables.

Consider the following partial computer output from a simple linear regression analysis. S = 0.4862 R-Sq = ______ Analysis of Variance Calculate the MSE.

_____ distribution is used for testing the significance of the slope term.

_____ measures the strength of the linear relationship between the dependent and the independent variable.

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 Based on Two Samples

Experimental Design and Analysis of Variance

Chi-Square Tests

Multiple Regression

Model Building and Model Diagnostics

Time Series Forecasting

Process Improvement Using Control Charts

Nonparametric Methods

Decision Theory

Filters

Exam 13: Simple Linear Regression Analysis

A data set with 7 observations yielded the following.Use the simple linear regression model. = 21.57 = 68.31 = 188.9 = 5,140.23 = 590.83 SSE = 1.06 Find the estimated slope.

The correlation coefficient is the ratio of explained variation to total variation.

The slope of the simple linear regression equation represents the average change in the value of the dependent variable per unit change in the independent variable (X).

Which of the following is a violation of one of the major assumptions of the simple regression model?

If the points are tightly distributed around the regression line on a scatter diagram,then we can conclude that the changes in the value of the dependent variable _________ the independent variable (X).

A data set with 7 observations yielded the following.Use the simple linear regression model. = 21.57 = 68.31 = 188.9 = 5,140.23 = 590.83 SSE = 1.06 Determine the 95% confidence interval for the average value of Y when x = 3.25.

The following results were obtained from a simple regression analysis: = 37.2895 - (1.2024)X r2= .6744 sb = .2934 For each unit change in X (independent variable),the estimated change in Y (dependent variable)is equal to:

When using simple linear regression,we would like to use confidence intervals for the _____ and prediction intervals for the _____ at a given value of x.

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. = 30 = 104 = 40 = 178 = 134 Determine SSE,SS (Total)

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

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

An experiment was performed on a certain metal to determine if the strength is a function of heating time.The simple linear regression equation is = 1 + 1X.The time is in minutes and the strength is measured in pounds per square inch. Provide a managerial interpretation of the slope.

_____ is a statistical technique in which we use observed data to relate a dependent variable to one or more predictor (independent)variables.

Consider the following partial computer output from a simple linear regression analysis. S = 0.4862 R-Sq = ______ Analysis of Variance Calculate the MSE.

_____ distribution is used for testing the significance of the slope term.

_____ measures the strength of the linear relationship between the dependent and the independent variable.

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 Based on Two Samples

Experimental Design and Analysis of Variance

Chi-Square Tests

Multiple Regression

Model Building and Model Diagnostics

Time Series Forecasting

Process Improvement Using Control Charts

Nonparametric Methods

Decision Theory

Filters

The following results were obtained from a simple regression analysis: = 37.2895 - (1.2024)X r²= .6744 s_b = .2934 For each unit change in X (independent variable),the estimated change in Y (dependent variable)is equal to:

When using simple linear regression,we would like to use confidence intervals for the _ and prediction intervals for the _ at a given value of x.

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