Question 1

Which of the following is an advantage of using the TREND() function versus the regression tool?

Accepted Answer

A)  The TREND() function provides more statistical information. 
B)  The TREND() function handles multiple dependent variable data. 
C)  The TREND() function is dynamically updated when input to the function changes. 
D)  The TREND() function does not use a least squares regression line. 
A)  The TREND() function provides more statistical information. 
B)  The TREND() function handles multiple dependent variable data. 
C)  The TREND() function is dynamically updated when input to the function changes. 
D)  The TREND() function does not use a least squares regression line.

Question 2

Exhibit 9.3
The following questions are based on the problem description and spreadsheet below.
A researcher is interested in determining how many calories young men consume. She measured the age of the individuals and recorded how much food they ate each day for a month. The average daily consumption was recorded as the dependent variable. She has developed the following Excel spreadsheet of the results.  
-Refer to Exhibit 9.3. Test the significance of the model and explain which values you used to reach your conclusions.

Accepted Answer

The regression model is signif

Question 3

The standard prediction error is

Accepted Answer

A)  always smaller than the standard error. 
B)  used to construct confidence intervals for predicted values. 
C)  measures the variability in the predicted values. 
D)  all of these. 
A)  always smaller than the standard error. 
B)  used to construct confidence intervals for predicted values. 
C)  measures the variability in the predicted values. 
D)  all of these.

Question 4

In regression analysis, the total variation is:

Accepted Answer

A)  the sum of the squared deviations of each value of y from the mean of x 
B)  the sum of the explained variation and unexplained variation 
C)  the standard error of the forecast 
D)  equal to R2 
A)  the sum of the squared deviations of each value of y from the mean of x 
B)  the sum of the explained variation and unexplained variation 
C)  the standard error of the forecast 
D)  equal to R2

Question 5

The R2 statistic

Accepted Answer

A)  varies between −1 and 1. 
B)  compares the regression sum of squares to the total sum of squares. 
C)  accounts for the number of parameters in the regression model. 
D)  is the ratio of the error sum of squares to the regression sum of squares. 
A)  varies between −1 and 1. 
B)  compares the regression sum of squares to the total sum of squares. 
C)  accounts for the number of parameters in the regression model. 
D)  is the ratio of the error sum of squares to the regression sum of squares.

Question 6

Which of the following cannot be negative?

Accepted Answer

A)  coefficient of determination 
B)  coefficient of correlation 
C)  coefficient of the independent variable, x, in the regression equation 
D)  y-intercept in the regression equation 
A)  coefficient of determination 
B)  coefficient of correlation 
C)  coefficient of the independent variable, x, in the regression equation 
D)  y-intercept in the regression equation

Question 7

Exhibit 9.6
The partial regression output below applies to the following questions.  
-Refer to Exhibit 9.6. What is the F-statistic value?

Accepted Answer

The answer of Exhibit 9.6
The partial regression output below applies...

Question 8

Exhibit 9.5
The following questions are based on the description and spreadsheet below.
An analyst has identified 3 independent variables (XS1U1B11S1U1B0, XS1U1B12S1U1B0,XS1U1B13S1U1B0) which might be used to predict Y. He has computed the regression equations using all of the variables and the results are summarized in the following table.  
-Refer to Exhibit 9.5. Based on the data in the table which is the best model for the charity to use? Explain which values you used to reach your conclusion.

Accepted Answer

The model with X₂ and

Question 9

Exhibit 9.3
The following questions are based on the problem description and spreadsheet below.
A researcher is interested in determining how many calories young men consume. She measured the age of the individuals and recorded how much food they ate each day for a month. The average daily consumption was recorded as the dependent variable. She has developed the following Excel spreadsheet of the results.  
-Refer to Exhibit 9.3. Predict the mean number of calories consumed by a 19 year old man.

Accepted Answer

The answer of Exhibit 9.3
The following questions are based on...

Question 10

R2 is calculated as

Accepted Answer

A)  ESS/TSS 
B)  1 − (RSS/TSS) 
C)  RSS/ESS 
D)  RSS/TSS 
A)  ESS/TSS 
B)  1 − (RSS/TSS) 
C)  RSS/ESS 
D)  RSS/TSS

Question 11

​In regression analysis, we consider models of the form: Y = f(X1, X2, ..., Xk) + $\varepsilon$

Accepted Answer

A) True 
 B)False

Question 12

How many independent variables are there in simple regression analysis?

Accepted Answer

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

Question 13

The adjusted R2 statistic

Accepted Answer

A)  is equal to the value of unadjusted R2 
B)  adjusts R2 for the degrees of freedom in the multiple regression model 
C)  accounts for the parameters in the multiple regression model 
D)  is always greater than R2 unadjusted 
A)  is equal to the value of unadjusted R2 
B)  adjusts R2 for the degrees of freedom in the multiple regression model 
C)  accounts for the parameters in the multiple regression model 
D)  is always greater than R2 unadjusted

Which of the following is an advantage of using the TREND() function versus the regression tool?

The standard prediction error is

In regression analysis, the total variation is:

The R² statistic

Which of the following cannot be negative?

Exhibit 9.6 The partial regression output below applies to the following questions. -Refer to Exhibit 9.6. What is the F-statistic value?

R² is calculated as

In regression analysis, we consider models of the form: Y = f(X₁, X₂, ..., X_k) + $\varepsilon$

How many independent variables are there in simple regression analysis?

The adjusted R² statistic

Introduction to Modeling and Decision Analysis

Introduction to Optimization and Linear Programming

Modeling and Solving Lp Problems in a Spreadsheet

Sensitivity Analysis and the Simplex Method

Network Modeling

Integer Linear Programming

Goal Programming and Multiple Objective Optimization

Nonlinear Programming Evolutionary Optimization

Data Mining

Time Series Forecasting

Introduction to Simulation Using Analytic Solver Platform

Queuing Theory

Decision Analysis

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Exam 9: Regression Analysis

Which of the following is an advantage of using the TREND() function versus the regression tool?

The standard prediction error is

In regression analysis, the total variation is:

The R2 statistic

Which of the following cannot be negative?

Exhibit 9.6 The partial regression output below applies to the following questions. -Refer to Exhibit 9.6. What is the F-statistic value?

R2 is calculated as

​In regression analysis, we consider models of the form: Y = f(X1, X2, ..., Xk) + ε\varepsilonε

How many independent variables are there in simple regression analysis?

The adjusted R2 statistic

Introduction to Modeling and Decision Analysis

Introduction to Optimization and Linear Programming

Modeling and Solving Lp Problems in a Spreadsheet

Sensitivity Analysis and the Simplex Method

Network Modeling

Integer Linear Programming

Goal Programming and Multiple Objective Optimization

Nonlinear Programming Evolutionary Optimization

Data Mining

Time Series Forecasting

Introduction to Simulation Using Analytic Solver Platform

Queuing Theory

Decision Analysis

Project Management Online

Filters

The R² statistic

R² is calculated as

In regression analysis, we consider models of the form: Y = f(X₁, X₂, ..., X_k) + $\varepsilon$

The adjusted R² statistic