Question 1

In simple linear regression, if the correlation coefficient is a positive value, then the slope of the estimated regression line

Accepted Answer

A) must also be positive 
B) can be either negative or positive 
C) can be zero 
D) must be negative 
E) none of the above 
A) must also be positive 
B) can be either negative or positive 
C) can be zero 
D) must be negative 
E) none of the above

Question 2

5% of the values in an F distribution with numerator degrees of freedom = 3 and denominator degrees of freedom = 12 are greater than ___.

Accepted Answer

A) 3.634 
B) 4.451 
C) 6.112 
D) 6.226 
E) 3.490 
A) 3.634 
B) 4.451 
C) 6.112 
D) 6.226 
E) 3.490

Question 3

The coefficient of determination r2, a measure of the goodness of fit of the estimated regression equation, is the ratio of the explained variation in y (SSR) to the total variation in y (SST), and takes on values between 0 and 1.

Accepted Answer

A) True 
 B)False

Question 4

The square root of the Mean Square Error (MSE) gives the standard error of estimate in regression analysis.

Accepted Answer

A) True 
 B)False

Question 5

The mean square in an Analysis of Variance (ANOVA) for multiple regression is the explained sum of squares (MSR) divided by the unexplained sum of squares (MSE).

Accepted Answer

A) True 
 B)False

Question 6

A regression analysis involved 6 independent variables and 27 observations.The t distribution in which we will find the critical value of t for testing the significance of each of the independent variable coefficients will have

Accepted Answer

A) 20 degrees of freedom 
B) 21 degrees of freedom 
C) 26 degrees of freedom 
D) 27 degrees of freedom 
E) none of the above 
A) 20 degrees of freedom 
B) 21 degrees of freedom 
C) 26 degrees of freedom 
D) 27 degrees of freedom 
E) none of the above

Question 7

A regression analysis linking demand (y in 1000 units) to price (x1 in dollars) and advertising (x2 in $1000s) resulted in the following equation: estimated Y = 9 - 5x1 + 2x2.This equation implies that a $1 increase in price can be associated with a ____ in demand.

Accepted Answer

A) 9000 - 5000 = 4000 unit increase 
B) 9000 unit decrease 
C) 9000 + 5000 = 14,000 unit decrease 
D) 5,000 unit decrease 
E) none of the above 
A) 9000 - 5000 = 4000 unit increase 
B) 9000 unit decrease 
C) 9000 + 5000 = 14,000 unit decrease 
D) 5,000 unit decrease 
E) none of the above

Question 8

In multiple regression analysis

Accepted Answer

A) there can be any number of dependent variables but only one independent variable 
B) there must be only one independent variable 
C) the coefficient of determination must be larger than 1 
D) there can be several independent variables, but only one dependent variable 
E) none of the above 
A) there can be any number of dependent variables but only one independent variable 
B) there must be only one independent variable 
C) the coefficient of determination must be larger than 1 
D) there can be several independent variables, but only one dependent variable 
E) none of the above

Question 9

A variable that takes on the values of 0 or 1 and is used to incorporate the effect of qualitative variables in a regression model is called a dummy variable.

Accepted Answer

A) True 
 B)False

Question 10

In multiple regression, adding more independent variables to the model will never decrease the value of r2.

Accepted Answer

A) True 
 B)False

Question 11

Introducing a series of highly correlated independent variables into a regression analysis will make it difficult to interpret the estimated regression coefficients because they may tend to fluctuate widely in response to small changes in the model or data set.

Accepted Answer

A) True 
 B)False

Question 12

A regression analysis involved 5 independent variables and 15 observations..In using the F table to find the critical value of F for testing the 'all s are 0' null hypothesis, the denominator degrees of freedom should be

Accepted Answer

A) 9 
B) 10 
C) 14 
D) 4 
E) none of the above 
A) 9 
B) 10 
C) 14 
D) 4 
E) none of the above

Question 13

In simple linear regression, a least squares regression line

Accepted Answer

A) assumes a relationship between the slope of x and the intercept of y 
B) may be used to predict a value of y if the corresponding x value is given 
C) must be linear, upward-sloping and have a positive y-intercept 
D) minimizes the sum of the deviations between the observed value of y and the estimated value of y 
E) all of the above 
A) assumes a relationship between the slope of x and the intercept of y 
B) may be used to predict a value of y if the corresponding x value is given 
C) must be linear, upward-sloping and have a positive y-intercept 
D) minimizes the sum of the deviations between the observed value of y and the estimated value of y 
E) all of the above

In simple linear regression, if the correlation coefficient is a positive value, then the slope of the estimated regression line

5% of the values in an F distribution with numerator degrees of freedom = 3 and denominator degrees of freedom = 12 are greater than ___.

The coefficient of determination r², a measure of the goodness of fit of the estimated regression equation, is the ratio of the explained variation in y (SSR) to the total variation in y (SST), and takes on values between 0 and 1.

The square root of the Mean Square Error (MSE) gives the standard error of estimate in regression analysis.

The mean square in an Analysis of Variance (ANOVA) for multiple regression is the explained sum of squares (MSR) divided by the unexplained sum of squares (MSE).

A regression analysis involved 6 independent variables and 27 observations.The t distribution in which we will find the critical value of t for testing the significance of each of the independent variable coefficients will have

A regression analysis linking demand (y in 1000 units) to price (x₁ in dollars) and advertising (x₂ in $1000s) resulted in the following equation: estimated Y = 9 - 5x₁ + 2x₂.This equation implies that a $1 increase in price can be associated with a ____ in demand.

In multiple regression analysis

A variable that takes on the values of 0 or 1 and is used to incorporate the effect of qualitative variables in a regression model is called a dummy variable.

In multiple regression, adding more independent variables to the model will never decrease the value of r².

Introducing a series of highly correlated independent variables into a regression analysis will make it difficult to interpret the estimated regression coefficients because they may tend to fluctuate widely in response to small changes in the model or data set.

A regression analysis involved 5 independent variables and 15 observations..In using the F table to find the critical value of F for testing the 'all s are 0' null hypothesis, the denominator degrees of freedom should be

In simple linear regression, a least squares regression line

An Introduction to Statistics

Descriptive Statistics I: Elementary Data Presentation and Description

Descriptive Statistics II: Additional Descriptive Measures and Data Displays

Probability

Discrete Probability Distributions

Continuous Probability Distributions

Statistical Inference: Estimating a Population Mean

Interval Estimates for Proportions, Mean Differences and Proportion Differences

Statistical Hypothesis Testing: Hypothesis Tests for a Population Mean

Hypothesis Tests for Proportions, Mean Differences and Proportion Differences

Basic Regression Analysis

F Tests and Analysis of Variance

Experimental Designonline Only

Chi-Square Tests

Filters

Exam 12: Multiple Regression

In simple linear regression, if the correlation coefficient is a positive value, then the slope of the estimated regression line

5% of the values in an F distribution with numerator degrees of freedom = 3 and denominator degrees of freedom = 12 are greater than ___.

The coefficient of determination r2, a measure of the goodness of fit of the estimated regression equation, is the ratio of the explained variation in y (SSR) to the total variation in y (SST), and takes on values between 0 and 1.

The square root of the Mean Square Error (MSE) gives the standard error of estimate in regression analysis.

The mean square in an Analysis of Variance (ANOVA) for multiple regression is the explained sum of squares (MSR) divided by the unexplained sum of squares (MSE).

A regression analysis involved 6 independent variables and 27 observations.The t distribution in which we will find the critical value of t for testing the significance of each of the independent variable coefficients will have

A regression analysis linking demand (y in 1000 units) to price (x1 in dollars) and advertising (x2 in $1000s) resulted in the following equation: estimated Y = 9 - 5x1 + 2x2.This equation implies that a $1 increase in price can be associated with a ____ in demand.

In multiple regression analysis

A variable that takes on the values of 0 or 1 and is used to incorporate the effect of qualitative variables in a regression model is called a dummy variable.

In multiple regression, adding more independent variables to the model will never decrease the value of r2.

Introducing a series of highly correlated independent variables into a regression analysis will make it difficult to interpret the estimated regression coefficients because they may tend to fluctuate widely in response to small changes in the model or data set.

A regression analysis involved 5 independent variables and 15 observations..In using the F table to find the critical value of F for testing the 'all s are 0' null hypothesis, the denominator degrees of freedom should be

In simple linear regression, a least squares regression line

An Introduction to Statistics

Descriptive Statistics I: Elementary Data Presentation and Description

Descriptive Statistics II: Additional Descriptive Measures and Data Displays

Probability

Discrete Probability Distributions

Continuous Probability Distributions

Statistical Inference: Estimating a Population Mean

Interval Estimates for Proportions, Mean Differences and Proportion Differences

Statistical Hypothesis Testing: Hypothesis Tests for a Population Mean

Hypothesis Tests for Proportions, Mean Differences and Proportion Differences

Basic Regression Analysis

F Tests and Analysis of Variance

Experimental Designonline Only

Chi-Square Tests

Filters

The coefficient of determination r², a measure of the goodness of fit of the estimated regression equation, is the ratio of the explained variation in y (SSR) to the total variation in y (SST), and takes on values between 0 and 1.

A regression analysis linking demand (y in 1000 units) to price (x₁ in dollars) and advertising (x₂ in $1000s) resulted in the following equation: estimated Y = 9 - 5x₁ + 2x₂.This equation implies that a $1 increase in price can be associated with a ____ in demand.

In multiple regression, adding more independent variables to the model will never decrease the value of r².