Question 1

A least squares regression line

Accepted Answer

A) may be used to predict a value of y if the corresponding x value is given 
B) implies a cause-effect relationship between x and y 
C) can only be determined if a good linear relationship exists between x and y 
D) All of these answers are correct. 
A) may be used to predict a value of y if the corresponding x value is given 
B) implies a cause-effect relationship between x and y 
C) can only be determined if a good linear relationship exists between x and y 
D) All of these answers are correct.

Question 2

If the coefficient of determination is equal to 1, then the coefficient of correlation

Accepted Answer

A) must also be equal to 1 
B) can be either -1 or +1 
C) can be any value between -1 to +1 
D) must be -1 
A) must also be equal to 1 
B) can be either -1 or +1 
C) can be any value between -1 to +1 
D) must be -1

Question 3

Which of the following is correct?

Accepted Answer

A) SSE = SSR + SST 
B) SSR = SSE + SST 
C) SST = SSR + SSE 
D) SST = (SSR)2 
A) SSE = SSR + SST 
B) SSR = SSE + SST 
C) SST = SSR + SSE 
D) SST = (SSR)2

Question 4

Exhibit 14-6
You are given the following information about y and x.  
-A company has recorded data on the daily demand for its product (y in thousands of units) and the unit price (x in hundreds of dollars). A sample of 15 days demand and associated prices resulted in the following data.   
a.Using the above information, develop the least-squares estimated regression line and write the equation.
b.Compute the coefficient of determination.
c.Perform an F test and determine whether or not there is a significant relationship between demand and unit price. Let $\alpha$ = 0.05.
d.Would the demand ever reach zero? If yes, at what price would the demand be zero?

Accepted Answer

a.= 16.515 - 0.903x
b.r<sup>2<

Question 5

Exhibit 14-1
A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x).  
-Refer to Exhibit 14-1. The least squares estimate of b0 equals

Accepted Answer

A) 1 
B) -1 
C) 5.5 
D) 11 
A) 1 
B) -1 
C) 5.5 
D) 11

Question 6

Exhibit 14-4
The following information regarding a dependent variable (Y) and an independent variable (X) is provided.   SSE = 6
SST = 16
-Refer to Exhibit 14-4. The coefficient of determination is

Accepted Answer

A) 0.7096 
B) - 0.7906 
C) 0.625 
D) 0.375 
A) 0.7096 
B) - 0.7906 
C) 0.625 
D) 0.375

Question 7

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 answers 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 answers is correct.

Question 8

The proportion of the variation in the dependent variable y that is explained by the estimated regression equation is measured by the

Accepted Answer

A) correlation coefficient 
B) standard error of the estimate 
C) coefficient of determination 
D) confidence interval estimate 
A) correlation coefficient 
B) standard error of the estimate 
C) coefficient of determination 
D) confidence interval estimate

Question 9

Exhibit 14-4
The following information regarding a dependent variable (Y) and an independent variable (X) is provided.   SSE = 6
SST = 16
-Refer to Exhibit 14-4. The least squares estimate of the Y intercept is

Accepted Answer

A) 1 
B) 2 
C) 3 
D) 4 
A) 1 
B) 2 
C) 3 
D) 4

Question 10

Exhibit 14-4
The following information regarding a dependent variable (Y) and an independent variable (X) is provided.   SSE = 6
SST = 16
-Refer to Exhibit 14-4. The coefficient of correlation is

Accepted Answer

A) 0.7906 
B) - 0.7906 
C) 0.625 
D) 0.375 
A) 0.7906 
B) - 0.7906 
C) 0.625 
D) 0.375

Question 11

A data point (observation) that does not fit the trend shown by the remaining data is called a (an)

Accepted Answer

A) residual 
B) outlier 
C) point estimate 
D) None of the other answers is correct. 
A) residual 
B) outlier 
C) point estimate 
D) None of the other answers is correct.

Question 12

In simple linear regression, r2 is the

Accepted Answer

A) estimated regression equation 
B) coefficient of correlation 
C) sum of the squared residuals 
D) coefficient of determination 
A) estimated regression equation 
B) coefficient of correlation 
C) sum of the squared residuals 
D) coefficient of determination

Question 13

Exhibit 14-2
You are given the following information about y and x.  
-Refer to Exhibit 14-2. The sample correlation coefficient equals

Accepted Answer

A) -86.667 
B) -0.99705 
C) 0.9941 
D) 0.99705 
A) -86.667 
B) -0.99705 
C) 0.9941 
D) 0.99705

Question 14

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 zero. 
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) All are required assumptions about the error term. 
A) The expected value of the error term is zero. 
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) All are required assumptions about the error term.

Question 15

As the goodness of fit for the estimated regression equation increases,

Accepted Answer

A) the absolute value of the regression equation's slope increases 
B) the value of the regression equation's y intercept decreases 
C) the value of the coefficient of determination increases 
D) the value of the correlation coefficient increases 
A) the absolute value of the regression equation's slope increases 
B) the value of the regression equation's y intercept decreases 
C) the value of the coefficient of determination increases 
D) the value of the correlation coefficient increases

Question 16

Exhibit 14-2
You are given the following information about y and x.  
-Refer to Exhibit 14-2. The least squares estimate of b1 equals

Accepted Answer

A) -0.7647 
B) -0.13 
C) 21.4 
D) 16.412 
A) -0.7647 
B) -0.13 
C) 21.4 
D) 16.412

Question 17

Exhibit 14-6
You are given the following information about y and x.  
-Given below are seven observations collected in a regression study on two variables, x (independent variable) and y (dependent variable). Use Excel's Regression Tool to construct a residual plot and use it to determine if any model assumption have been violated.

Accepted Answer

@#IMG-DLM& The constant varian

Question 18

A regression analysis between sales (y in $1000) and advertising (x in dollars) resulted in the following equation   = 50,000 + 6x The above equation implies that an

Accepted Answer

A) increase of $6 in advertising is associated with an increase of $6,000 in sales 
B) increase of $1 in advertising is associated with an increase of $6 in sales 
C) increase of $1 in advertising is associated with an increase of $56,000 in sales 
D) increase of $1 in advertising is associated with an increase of $6,000 in sales 
A) increase of $6 in advertising is associated with an increase of $6,000 in sales 
B) increase of $1 in advertising is associated with an increase of $6 in sales 
C) increase of $1 in advertising is associated with an increase of $56,000 in sales 
D) increase of $1 in advertising is associated with an increase of $6,000 in sales

Question 19

Exhibit 14-3
Regression analysis was applied between sales data (in $1,000s) and advertising data (in $100s) and the following information was obtained.  
-Refer to Exhibit 14-3. The t statistic for testing the significance of the slope is

Accepted Answer

A) 1.80 
B) 1.96 
C) 6.709 
D) 0.555 
A) 1.80 
B) 1.96 
C) 6.709 
D) 0.555

Question 20

Exhibit 14-6
You are given the following information about y and x.  
-The following data represent the number of flash drives sold per day at a local computer shop and their prices.   
a.Develop a least-squares regression line and explain what the slope of the line indicates.
b.Compute the coefficient of determination and comment on the strength of relationship between x and y.
c.Compute the sample correlation coefficient between the price and the number of flash drives sold. Use $\alpha$= 0.01 to test the relationship between x and y.

Accepted Answer

a.= 29.7857 - 0.7286x
The slope indicate

A least squares regression line

If the coefficient of determination is equal to 1, then the coefficient of correlation

Which of the following is correct?

Exhibit 14-1 A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x). -Refer to Exhibit 14-1. The least squares estimate of b₀ equals

Exhibit 14-4 The following information regarding a dependent variable (Y) and an independent variable (X) is provided. SSE = 6 SST = 16 -Refer to Exhibit 14-4. The coefficient of determination is

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

The proportion of the variation in the dependent variable y that is explained by the estimated regression equation is measured by the

Exhibit 14-4 The following information regarding a dependent variable (Y) and an independent variable (X) is provided. SSE = 6 SST = 16 -Refer to Exhibit 14-4. The least squares estimate of the Y intercept is

Exhibit 14-4 The following information regarding a dependent variable (Y) and an independent variable (X) is provided. SSE = 6 SST = 16 -Refer to Exhibit 14-4. The coefficient of correlation is

A data point (observation) that does not fit the trend shown by the remaining data is called a (an)

In simple linear regression, r²is the

Exhibit 14-2 You are given the following information about y and x. -Refer to Exhibit 14-2. The sample correlation coefficient equals

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

As the goodness of fit for the estimated regression equation increases,

Exhibit 14-2 You are given the following information about y and x. -Refer to Exhibit 14-2. The least squares estimate of b₁ equals

A regression analysis between sales (y in $1000) and advertising (x in dollars) resulted in the following equation = 50,000 + 6x The above equation implies that an

Exhibit 14-3 Regression analysis was applied between sales data (in $1,000s) and advertising data (in $100s) and the following information was obtained. -Refer to Exhibit 14-3. The t statistic for testing the significance of the slope is

Data and Statistics

Descriptive Statistics: Tabular and Graphical Displays

Descriptive Statistics: Numerical Measures

Introduction to Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling and Sampling Distributions

Interval Estimation

Hypothesis Tests

Inference About Means and Proportions With Two Populations

Inferences About Population Variances

Tests of Goodness of Fit, Independence and Multiple Proportions

Experimental Design and Analysis of Variance

Multiple Regression

Regression Analysis: Model Building

Time Series Analysis and Forecasting

Nonparametric Methods

Statistical Methods for Quality Control

Decision Analysis

Sample Survey

Filters

Exam 14: Simple Linear Regression

A least squares regression line

If the coefficient of determination is equal to 1, then the coefficient of correlation

Which of the following is correct?

Exhibit 14-1 A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x). -Refer to Exhibit 14-1. The least squares estimate of b0 equals

Exhibit 14-4 The following information regarding a dependent variable (Y) and an independent variable (X) is provided. SSE = 6 SST = 16 -Refer to Exhibit 14-4. The coefficient of determination is

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

The proportion of the variation in the dependent variable y that is explained by the estimated regression equation is measured by the

Exhibit 14-4 The following information regarding a dependent variable (Y) and an independent variable (X) is provided. SSE = 6 SST = 16 -Refer to Exhibit 14-4. The least squares estimate of the Y intercept is

Exhibit 14-4 The following information regarding a dependent variable (Y) and an independent variable (X) is provided. SSE = 6 SST = 16 -Refer to Exhibit 14-4. The coefficient of correlation is

A data point (observation) that does not fit the trend shown by the remaining data is called a (an)

In simple linear regression, r2 is the

Exhibit 14-2 You are given the following information about y and x. -Refer to Exhibit 14-2. The sample correlation coefficient equals

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

As the goodness of fit for the estimated regression equation increases,

Exhibit 14-2 You are given the following information about y and x. -Refer to Exhibit 14-2. The least squares estimate of b1 equals

A regression analysis between sales (y in $1000) and advertising (x in dollars) resulted in the following equation = 50,000 + 6x The above equation implies that an

Exhibit 14-3 Regression analysis was applied between sales data (in $1,000s) and advertising data (in $100s) and the following information was obtained. -Refer to Exhibit 14-3. The t statistic for testing the significance of the slope is

Data and Statistics

Descriptive Statistics: Tabular and Graphical Displays

Descriptive Statistics: Numerical Measures

Introduction to Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling and Sampling Distributions

Interval Estimation

Hypothesis Tests

Inference About Means and Proportions With Two Populations

Inferences About Population Variances

Tests of Goodness of Fit, Independence and Multiple Proportions

Experimental Design and Analysis of Variance

Multiple Regression

Regression Analysis: Model Building

Time Series Analysis and Forecasting

Nonparametric Methods

Statistical Methods for Quality Control

Decision Analysis

Sample Survey

Filters

Exhibit 14-1 A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x). -Refer to Exhibit 14-1. The least squares estimate of b₀ equals

In simple linear regression, r²is the

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

Exhibit 14-2 You are given the following information about y and x. -Refer to Exhibit 14-2. The least squares estimate of b₁ equals