Question 1

Error sum of squares (ESS) is computed as

Accepted Answer

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

Question 2

When using the Regression tool in Excel the dependent variable is entered as the

Accepted Answer

A)  X-range. 
B)  Y-range. 
C)  dependent-range. 
D)  independent-range. 
A)  X-range. 
B)  Y-range. 
C)  dependent-range. 
D)  independent-range.

Question 3

The terms b0 and b1 are

Accepted Answer

A)  estimated population parameters. 
B)  estimated intercept and slope values, respectively. 
C)  random variables. 
D)  all of these. 
A)  estimated population parameters. 
B)  estimated intercept and slope values, respectively. 
C)  random variables. 
D)  all of these.

Question 4

The term multicollinearity is used to describe the situation when the independent variables in a regression model are correlated among themselves.

Accepted Answer

A) True 
 B)False

Question 5

Regression analysis is a modeling technique

Accepted Answer

A)  that assumes all data is normally distributed. 
B)  for analyzing the relationship between dependent and independent variables. 
C)  for examining linear trend data only. 
D)  for capturing uncertainty in predicted values of Y. 
A)  that assumes all data is normally distributed. 
B)  for analyzing the relationship between dependent and independent variables. 
C)  for examining linear trend data only. 
D)  for capturing uncertainty in predicted values of Y.

Question 6

The β1 term indicates

Accepted Answer

A)  the average change in Y for a unit change in X. 
B)  the Y value for a given value of X. 
C)  the change in observed X for a given change in Y. 
D)  the Y value when X equals zero. 
A)  the average change in Y for a unit change in X. 
B)  the Y value for a given value of X. 
C)  the change in observed X for a given change in Y. 
D)  the Y value when X equals zero.

Question 7

The actual value of a dependent variable will generally differ from the regression equation estimate due to

Accepted Answer

A)  unaccounted for random variation. 
B)  the inability of the nonlinear Solver to find optimal values. 
C)  not building the regression model with enough data. 
D)  the model R2 not equal to 1. 
A)  unaccounted for random variation. 
B)  the inability of the nonlinear Solver to find optimal values. 
C)  not building the regression model with enough data. 
D)  the model R2 not equal to 1.

Question 8

What does regression analysis attempt to establish?

Accepted Answer

A)  a mathematical relationship between a dependent variable, for which future values will be forecast, and one or more independent variables with known values 
B)  linearity in the relationship between independent variables 
C)  linearity in the relationship between a dependent variable and a set of independent variables 
D)  multicollinearity 
A)  a mathematical relationship between a dependent variable, for which future values will be forecast, and one or more independent variables with known values 
B)  linearity in the relationship between independent variables 
C)  linearity in the relationship between a dependent variable and a set of independent variables 
D)  multicollinearity

Question 9

The reason an analyst creates a regression model is

Accepted Answer

A)  to determine the errors in the data collected. 
B)  to predict a dependent variable value given specific independent variable values. 
C)  to predict an independent variable value given specific dependent variable values. 
D)  to verify the errors are normally distributed. 
A)  to determine the errors in the data collected. 
B)  to predict a dependent variable value given specific independent variable values. 
C)  to predict an independent variable value given specific dependent variable values. 
D)  to verify the errors are normally distributed.

Question 10

On average, the differences between the actual and predicted values of Y

Accepted Answer

A)  are equal to b0. 
B)  sum to an unknown value. 
C)  are distributed uniformly. 
D)  sum to zero. 
A)  are equal to b0. 
B)  sum to an unknown value. 
C)  are distributed uniformly. 
D)  sum to zero.

Question 11

The researcher would like to build a prediction interval on the calories consumed by an 18 year old man. What formula should be entered in cells B17:F21 of the following spreadsheet to compute this prediction interval? Partial results of the Regression analysis of the data are provided below.

Accepted Answer

The answer of The researcher would like to build a...

Question 12

The terms β0 and β1 are referred to as

Accepted Answer

A)  sample statistics 
B)  random variables 
C)  population variables 
D)  population parameters 
A)  sample statistics 
B)  random variables 
C)  population variables 
D)  population parameters

Question 13

The company would like to build a prediction interval on the pressure for a can with a temperature of 125 degrees. What formula should be entered in cells B17:F21 of the following spreadsheet to compute this prediction interval? Partial results of the Regression analysis of the data are provided below.

Accepted Answer

The answer of The company would like to build a...

Question 14

Exhibit 9.6
The partial regression output below applies to the following questions.  
-Refer to Exhibit 9.6. What is the MS for Residual?

Accepted Answer

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

Question 15

Based on the following regression output, what is the equation of the regression line?

Accepted Answer

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

Question 16

R2 measures

Accepted Answer

A)  the percentage of variability in the dependent variable, Y, explained by the model 
B)  the unexplained variability 
C)  the ratio of RSS/ESS 
D)  the model sophistication 
A)  the percentage of variability in the dependent variable, Y, explained by the model 
B)  the unexplained variability 
C)  the ratio of RSS/ESS 
D)  the model sophistication

Question 17

Residuals are assumed to be

Accepted Answer

A)  dependent, uniformly distributed random variables. 
B)  independent, uniformly distributed random variables. 
C)  dependent, normally distributed random variables. 
D)  independent, normally distributed random variables. 
A)  dependent, uniformly distributed random variables. 
B)  independent, uniformly distributed random variables. 
C)  dependent, normally distributed random variables. 
D)  independent, normally distributed random variables.

Question 18

The forecasting model that makes use of the least squares method is called

Accepted Answer

A)  regression 
B)  naive approach 
C)  moving average 
D)  exponential smoothing 
A)  regression 
B)  naive approach 
C)  moving average 
D)  exponential smoothing

Question 19

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. Interpret the meaning of the "Lower 95%" and "Upper 95%" terms in cells F16:G16 of the spreadsheet.

Accepted Answer

We are 95% confident

Question 20

The value of adjusted ​R2 can be negative.

Accepted Answer

A) True 
 B)False

Error sum of squares (ESS) is computed as

When using the Regression tool in Excel the dependent variable is entered as the

The terms b₀ and b₁ are

The term multicollinearity is used to describe the situation when the independent variables in a regression model are correlated among themselves.

Regression analysis is a modeling technique

The β₁ term indicates

The actual value of a dependent variable will generally differ from the regression equation estimate due to

What does regression analysis attempt to establish?

The reason an analyst creates a regression model is

On average, the differences between the actual and predicted values of Y

The researcher would like to build a prediction interval on the calories consumed by an 18 year old man. What formula should be entered in cells B17:F21 of the following spreadsheet to compute this prediction interval? Partial results of the Regression analysis of the data are provided below.

The terms β₀ and β₁ are referred to as

Exhibit 9.6 The partial regression output below applies to the following questions. -Refer to Exhibit 9.6. What is the MS for Residual?

Based on the following regression output, what is the equation of the regression line?

R² measures

Residuals are assumed to be

The forecasting model that makes use of the least squares method is called

The value of adjusted R² can be negative.

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

Exam 9: Regression Analysis

Error sum of squares (ESS) is computed as

When using the Regression tool in Excel the dependent variable is entered as the

The terms b0 and b1 are

The term multicollinearity is used to describe the situation when the independent variables in a regression model are correlated among themselves.

Regression analysis is a modeling technique

The β1 term indicates

The actual value of a dependent variable will generally differ from the regression equation estimate due to

What does regression analysis attempt to establish?

The reason an analyst creates a regression model is

On average, the differences between the actual and predicted values of Y

The researcher would like to build a prediction interval on the calories consumed by an 18 year old man. What formula should be entered in cells B17:F21 of the following spreadsheet to compute this prediction interval? Partial results of the Regression analysis of the data are provided below.

The terms β0 and β1 are referred to as

Exhibit 9.6 The partial regression output below applies to the following questions. -Refer to Exhibit 9.6. What is the MS for Residual?

Based on the following regression output, what is the equation of the regression line?

R2 measures

Residuals are assumed to be

The forecasting model that makes use of the least squares method is called

The value of adjusted ​R2 can be negative.

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 terms b₀ and b₁ are

The β₁ term indicates

The terms β₀ and β₁ are referred to as

R² measures

The value of adjusted R² can be negative.