Question 1

The total sum of squares (TSS) is best defined as

Accepted Answer

A) the sums of squares of the dependent variables. 
B) the total variation of Y around its mean. 
C) the sums of squares of the predicted values. 
D) the variation of Y around its mean plus the variation of Y around the predicted values. 
A) the sums of squares of the dependent variables. 
B) the total variation of Y around its mean. 
C) the sums of squares of the predicted values. 
D) the variation of Y around its mean plus the variation of Y around the predicted values.

Question 2

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 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 coefficients ar

Question 4

The $\beta$1 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 5

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 6

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 7

The following questions are based on the problem description and spreadsheet below.
A company has built a regression model to predict the number of labor hours (YS1U1B1iS1U1B0) required to process a batch of parts (XS1U1B1iS1U1B0). It has developed the following Excel spreadsheet of the results.
  
-Refer to Exhibit 9.1. Predict the mean number of labor hours for a batch of 5 parts.

Accepted Answer

@#IMG-DLM& ₅ = 4.8400

Question 8

The regression line denotes the ____ between the dependent and independent variables.

Accepted Answer

A) unsystematic variation 
B) systematic variation 
C) random variation 
D) average variation 
A) unsystematic variation 
B) systematic variation 
C) random variation 
D) average variation

Question 9

The error term $\varepsilon$ in a regression model represents

Accepted Answer

A) a random error in the data. 
B) unsystematic variation in the dependent variable. 
C) variation not explained by the independent variables. 
D) all of these. 
A) a random error in the data. 
B) unsystematic variation in the dependent variable. 
C) variation not explained by the independent variables. 
D) all of these.

Question 10

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 11

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 12

The regression function indicates the

Accepted Answer

A) average value the dependent variable assumes for a given value of the independent variable. 
B) actual value the independent variable assumes for a given value of the dependent variable 
C) average value the dependent variable assumes for a given value of the dependent variable 
D) actual value the dependent variable assumes for a given value of the independent variable 
A) average value the dependent variable assumes for a given value of the independent variable. 
B) actual value the independent variable assumes for a given value of the dependent variable 
C) average value the dependent variable assumes for a given value of the dependent variable 
D) actual value the dependent variable assumes for a given value of the independent variable

Question 13

The terms b0 and b1 are referred to as

Accepted Answer

A) population variables. 
B) population parameters. 
C) estimated population variables. 
D) estimated population parameters. 
A) population variables. 
B) population parameters. 
C) estimated population variables. 
D) estimated population parameters.

Question 14

The regression residuals are computed as

Accepted Answer

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

Question 15

Based on the following regression output, what conclusion can you reach about $\beta$1?

Accepted Answer

A) $\beta$1 = 0, with P-value = 0.016353 
B) $\beta$1 $\neq$ 0, with P-value = 0.016353 
C) $\beta$1 = 0, with P-value = 0.000186 
D) $\beta$1 $\neq$ 0, with P-value = 0.000186 
A) $\beta$1 = 0, with P-value = 0.016353 
B) $\beta$1 $\neq$ 0, with P-value = 0.016353 
C) $\beta$1 = 0, with P-value = 0.000186 
D) $\beta$1 $\neq$ 0, with P-value = 0.000186

Question 16

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 17

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 18

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 19

The objective function in regression analysis is

Accepted Answer

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

Question 20

The following questions are based on the problem description and spreadsheet below.
A paint manufacturer is interested in knowing how much pressure (in pounds per square inch, PSI) builds up inside aerosol cans at various temperatures (degrees Fahrenheit). It has developed the following Excel spreadsheet of the results.
  
-Refer to Exhibit 9.2. Predict the mean pressure for a temperature of 120 degrees.

Accepted Answer

@#IMG-DLM& _i = 38.192

The total sum of squares (TSS) is best defined as

Residuals are assumed to be

The $\beta$ ₁ term indicates

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

The regression line denotes the ____ between the dependent and independent variables.

The error term $\varepsilon$ in a regression model represents

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

The regression function indicates the

The terms b₀ and b₁ are referred to as

The regression residuals are computed as

Based on the following regression output, what conclusion can you reach about $\beta$ ₁? $Based on the following regression output, what conclusion can you reach about \beta <sub>1</sub>?$

The standard prediction error is

Regression analysis is a modeling technique

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

The objective function in regression analysis is

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 and Evolutionary Optimization

Discriminant Analysis

Time Series Forecasting

Introduction to Simulation Using Risk Solver Platform

Queuing Theory

Decision Analysis

Project Management Online

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Exam 9: Regression Analysis

The total sum of squares (TSS) is best defined as

Residuals are assumed to be

The β\betaβ 1 term indicates

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

The regression line denotes the ____ between the dependent and independent variables.

The error term ε\varepsilonε in a regression model represents

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

The regression function indicates the

The terms b0 and b1 are referred to as

The regression residuals are computed as

Based on the following regression output, what conclusion can you reach about β\betaβ 1?

The standard prediction error is

Regression analysis is a modeling technique

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

The objective function in regression analysis is

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 and Evolutionary Optimization

Discriminant Analysis

Time Series Forecasting

Introduction to Simulation Using Risk Solver Platform

Queuing Theory

Decision Analysis

Project Management Online

Filters

The $\beta$ ₁ term indicates

The error term $\varepsilon$ in a regression model represents

The terms b₀ and b₁ are referred to as

Based on the following regression output, what conclusion can you reach about $\beta$ ₁? $Based on the following regression output, what conclusion can you reach about \beta <sub>1</sub>?$