Question 1

If the coefficient of determination is a positive value, then the regression equation

Accepted Answer

A) must have a positive slope 
B) must have a negative slope 
C) could have either a positive or a negative slope 
D) must have a positive y intercept 
A) must have a positive slope 
B) must have a negative slope 
C) could have either a positive or a negative slope 
D) must have a positive y intercept

Question 2

SSE can never be

Accepted Answer

A) larger than SST 
B) smaller than SST 
C) equal to 1 
D) equal to zero 
A) larger than SST 
B) smaller than SST 
C) equal to 1 
D) equal to zero

Question 3

Exhibit 14-6
You are given the following information about y and x.  
-Part of an Excel output relating X (independent variable) and Y (dependent variable) is shown below. Fill in all the blanks marked with "?".

Accepted Answer

The answer of Exhibit 14-6
You are given the following information...

Question 4

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 MSE is

Accepted Answer

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

Question 5

Part of an Excel output relating X (independent variable) and Y (dependent variable) is shown below. Fill in all the blanks marked with "?".

Accepted Answer

The answer of Part of an Excel output relating X...

Question 6

An observation that has a strong effect on the regression results is called a (an)

Accepted Answer

A) residual 
B) sum of squares error 
C) influential observation 
D) None of the other answers is correct. 
A) residual 
B) sum of squares error 
C) influential observation 
D) None of the other answers is correct.

Question 7

A procedure used for finding the equation of a straight line that provides the best approximation for the relationship between the independent and dependent variables is the

Accepted Answer

A) correlation analysis 
B) mean squares method 
C) least squares method 
D) most squares method 
A) correlation analysis 
B) mean squares method 
C) least squares method 
D) most squares method

Question 8

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.Perform an F test and determine if the price and the number of flash drives sold are related. Let $\alpha$ = 0.01.
b.Perform a t test and determine if the price and the number of flash drives sold are related. Let $\alpha$ = 0.01.

Accepted Answer

a.F = 29.624 > 16.26; p-value < .01; (Ex

Question 9

The least squares criterion is

Accepted Answer

A)   
B)   
C)   
D)   
A)   
B)   
C)   
D)

Question 10

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 to develop a scatter diagram and to compute the least squares estimated regression equation.

Accepted Answer

The answer of Exhibit 14-6
You are given the following information...

Question 11

Exhibit 14-6
You are given the following information about y and x.  
-Scott Bell Builders would like to predict the total number of labor hours spent framing a house based on the square footage of the house. The following data has been compiled on ten houses recently built.   
a. Develop the least-squares estimated regression equation that relates framing labor hours to house square footage.
b. Use the regression equation developed in part (a) to predict framing labor hours when the house size is 3350 square feet.

Accepted Answer

The answer of Exhibit 14-6
You are given the following information...

Question 12

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).   
a.Develop the least squares estimated regression equation.
b.At 95% confidence, perform a t test and determine whether or not the slope is significantly different from zero.
c.Perform an F test to determine whether or not the model is significant. Let $\alpha$ = 0.05.
d.Compute the coefficient of determination.

Accepted Answer

a.= 13.75 - 1.125x
b.t = -5.19

Question 13

If all the points of a scatter diagram lie on the least squares regression line, then the coefficient of determination for these variables based on this data is

Accepted Answer

A) 0 
B) 1 
C) either 1 or -1, depending upon whether the relationship is positive or negative 
D) could be any value between -1 and 1 
A) 0 
B) 1 
C) either 1 or -1, depending upon whether the relationship is positive or negative 
D) could be any value between -1 and 1

Question 14

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 slope is

Accepted Answer

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

Question 15

Exhibit 14-6
You are given the following information about y and x.  
-Refer to Exhibit 14-6. The sample correlation coefficient equals

Accepted Answer

A) -0.4364 
B) 0.4364 
C) -0.1905 
D) 0.1905 
A) -0.4364 
B) 0.4364 
C) -0.1905 
D) 0.1905

Question 16

A measure of the strength of the relationship between two variables is the

Accepted Answer

A) coefficient of determination 
B) slope b1 of the estimated regression line 
C) standard error of the estimate 
D) correlation coefficient 
A) coefficient of determination 
B) slope b1 of the estimated regression line 
C) standard error of the estimate 
D) correlation coefficient

Question 17

Exhibit 14-5
You are given the following information about y and x.  
-Refer to Exhibit 14-5. The least squares estimate of b1 (slope) equals

Accepted Answer

A) 1 
B) -1 
C) 6 
D) 5 
A) 1 
B) -1 
C) 6 
D) 5

Question 18

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 point estimate of y when x = 20 is

Accepted Answer

A) 0 
B) 31 
C) 9 
D) -9 
A) 0 
B) 31 
C) 9 
D) -9

Question 19

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 coefficient of determination equals

Accepted Answer

A) 0 
B) -1 
C) +1 
D) -0.5 
A) 0 
B) -1 
C) +1 
D) -0.5

Question 20

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 F statistic computed from the above data is

Accepted Answer

A) 3 
B) 45 
C) 48 
D) Not enough information is given to answer this question. 
A) 3 
B) 45 
C) 48 
D) Not enough information is given to answer this question.

If the coefficient of determination is a positive value, then the regression equation

SSE can never be

Exhibit 14-6 You are given the following information about y and x. -Part of an Excel output relating X (independent variable) and Y (dependent variable) is shown below. Fill in all the blanks marked with "?".

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 MSE is

Part of an Excel output relating X (independent variable) and Y (dependent variable) is shown below. Fill in all the blanks marked with "?".

An observation that has a strong effect on the regression results is called a (an)

A procedure used for finding the equation of a straight line that provides the best approximation for the relationship between the independent and dependent variables is the

The least squares criterion is

If all the points of a scatter diagram lie on the least squares regression line, then the coefficient of determination for these variables based on this data 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 least squares estimate of the slope is

Exhibit 14-6 You are given the following information about y and x. -Refer to Exhibit 14-6. The sample correlation coefficient equals

A measure of the strength of the relationship between two variables is the

Exhibit 14-5 You are given the following information about y and x. -Refer to Exhibit 14-5. The least squares estimate of b₁ (slope) equals

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 point estimate of y when x = 20 is

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 coefficient of determination equals

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 F statistic computed from the above data 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

If the coefficient of determination is a positive value, then the regression equation

SSE can never be

Exhibit 14-6 You are given the following information about y and x. -Part of an Excel output relating X (independent variable) and Y (dependent variable) is shown below. Fill in all the blanks marked with "?".

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 MSE is

Part of an Excel output relating X (independent variable) and Y (dependent variable) is shown below. Fill in all the blanks marked with "?".

An observation that has a strong effect on the regression results is called a (an)

A procedure used for finding the equation of a straight line that provides the best approximation for the relationship between the independent and dependent variables is the

The least squares criterion is

If all the points of a scatter diagram lie on the least squares regression line, then the coefficient of determination for these variables based on this data 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 least squares estimate of the slope is

Exhibit 14-6 You are given the following information about y and x. -Refer to Exhibit 14-6. The sample correlation coefficient equals

A measure of the strength of the relationship between two variables is the

Exhibit 14-5 You are given the following information about y and x. -Refer to Exhibit 14-5. The least squares estimate of b1 (slope) equals

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 point estimate of y when x = 20 is

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 coefficient of determination equals

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 F statistic computed from the above data 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 14-5 You are given the following information about y and x. -Refer to Exhibit 14-5. The least squares estimate of b₁ (slope) equals