Question 1

The first-order polynomial model is the same as the simple linear regression model.

Accepted Answer

A) True 
 B)False

Question 2

Write a formula for the fourth-order polynomial model.Would such a polynomial model tend to be practical for use with business data?

Accepted Answer

@#LAT-DLM& .Due to its complex

Question 3

If level of education has four possible categories,four qualitative variables would be needed to represent education in the regression model.

Accepted Answer

A) True 
 B)False

Question 4

Briefly discuss the best subset regression approach.

Accepted Answer

In the best subset regression approach,s

Question 5

Consider the model described by the equation $$E ( y ) = \beta _ { 0 } + \beta _ { 1 } x + \beta _ { 2 } x ^ { 2 } + \beta _ { 3 } x ^ { 3 }$$ .Which term provides a nonlinear component to the model enabling the line to reverse the direction of curvature?

Accepted Answer

A) $\beta _ { 0 }$ 
B) $\beta _ { 1 } x$ 
C) $\beta _ { 2 } x ^ { 2 }$ 
D) $\beta _ { 3 } x ^ { 3 }$ 
A) $\beta _ { 0 }$ 
B) $\beta _ { 1 } x$ 
C) $\beta _ { 2 } x ^ { 2 }$ 
D) $\beta _ { 3 } x ^ { 3 }$

Question 6

What is stepwise regression,and when is it desirable to make use of this multiple regression technique?

Accepted Answer

Stepwise regression is a multiple regres

Question 7

What is the general idea of stepwise regression?

Accepted Answer

The general idea of stepwise regression

Question 8

For the second-order polynomial model $E ( y ) = \beta _ { 0 } + \beta _ { 1 } x + \beta _ { 2 } x ^ { 2 }$ ,the shape of the curve will be determined by the relative sizes of $\beta _ { 1 }$ and $\beta _ { 2 }$ and on their signs.

Accepted Answer

A) True 
 B)False

Question 9

The shape of the model described by the equation $E ( y ) = \beta _ { 0 } + \beta _ { 1 } x + \beta _ { 2 } x ^ { 2 }$ could be:

Accepted Answer

A)  parabolic resembling an upright"U". 
B)  parabolic resembling an upside-down"U". 
C)  a straight line with an intercept $\beta _ { 0 }$ and slope $\beta _ { 2 } / \beta _ { 1 }$ . 
D)  a straight line with an intercept $\beta _ { 0 }$ and slope $\beta _ { 1 } / \beta _ { 2 } .$. 
E)  Both A and B. 
A)  parabolic resembling an upright"U". 
B)  parabolic resembling an upside-down"U". 
C)  a straight line with an intercept $\beta _ { 0 }$ and slope $\beta _ { 2 } / \beta _ { 1 }$ . 
D)  a straight line with an intercept $\beta _ { 0 }$ and slope $\beta _ { 1 } / \beta _ { 2 } .$. 
E)  Both A and B.

Question 10

Discuss some of the signals for the presence of multicollinearity.

Accepted Answer

There are several clues to the presence

Question 11

Three predictor variables are being considered for use in a linear regression model.Given the correlation matrix below,does it appear that multicollinearity could be a problem?
 $$\begin{array} { | l | l | l | l } 
\hline & x 1 & x ^ { 2 } & x 3 \
\hline x 1 & 1.000 & & \
\hline x 2 & 0.025 & 1.000 & \
\hline x ^ { 3 } & 0.968 & 0.897 & 1.000 \
\hline
\end{array}$$

Accepted Answer

Yes; It appears that multicoll

Question 12

In explaining students' test scores,which of the following independent variables would not best be represented by a dummy variable?

Accepted Answer

A)  Gender 
B)  Race 
C)  Number of hours studying for the test 
D)  Marital status 
A)  Gender 
B)  Race 
C)  Number of hours studying for the test 
D)  Marital status

Question 13

Multicollinearity is a situation in which the dependent variable is highly correlated with two or more of the independent variables in a multiple regression.

Accepted Answer

A) True 
 B)False

Question 14

For a sample of 200 recent credit-card customers of a company's on-line store,the following data are available: the dollar amount of merchandise ordered during the visit,how much time (minutes)the customer spent at the site during the purchase visit,and whether the customer used a Visa,Master Card,or other.Describe the format of a linear regression equation for estimating the dollar amount of the order on the basis of the other variables described above.If any qualitative variables are used,indicate the strategy for coding them.

Accepted Answer

Although we have three types of credit c

Question 15

The regression model $\hat { Y }$ = 160 + 8x1 - 5x2 has been fitted to a set of data.If x2 = 10,what will be the effect on $\hat { Y }$ if x1 increases by 1 unit? 
$\hat { Y }$ will ____________________ by ____________________

Accepted Answer

Question 16

The model $\hat{ Y }$ = b0 + b1x1 + b2x2 is referred to as the:

Accepted Answer

A)  first order model with one predictor variable. 
B)  first order model with two predictor variables. 
C)  second order model with one predictor variable. 
D)  second order model with two predictor variables. 
A)  first order model with one predictor variable. 
B)  first order model with two predictor variables. 
C)  second order model with one predictor variable. 
D)  second order model with two predictor variables.

Question 17

How do we test the reliability of a model?

Accepted Answer

The model can be tested by applying it t

Question 18

The model $\hat { Y }$ = $b _ { 0 } x _ { 1 } ^ { b } 1 x _ { 2 } ^ { b _ { 2 } }$ is referred to as a multiplicative model with two predictor variables.

Accepted Answer

A) True 
 B)False

Question 19

Which of the following statements are important steps in selecting a model?

Accepted Answer

A)  Specify the dependent variable and determine the goal for the analysis. 
B)  Specify possible predictor variables and collect the data. 
C)  Specify the candidate models,and for each candidate model decide which of the available predictor variables will be included in the model. 
D)  Select a model,evaluate its suitability and test its reliability. 
E)  All of these. 
A)  Specify the dependent variable and determine the goal for the analysis. 
B)  Specify possible predictor variables and collect the data. 
C)  Specify the candidate models,and for each candidate model decide which of the available predictor variables will be included in the model. 
D)  Select a model,evaluate its suitability and test its reliability. 
E)  All of these.

Question 20

If the goal for the regression analysis is to interpret partial regression coefficients in an attempt to better understand the relationship between the dependent variable and one or more of the predictor variables,it will be desirable to build a smaller model with predictor variables that are more independent from each other.

Accepted Answer

A) True 
 B)False

The first-order polynomial model is the same as the simple linear regression model.

Write a formula for the fourth-order polynomial model.Would such a polynomial model tend to be practical for use with business data?

If level of education has four possible categories,four qualitative variables would be needed to represent education in the regression model.

Briefly discuss the best subset regression approach.

Consider the model described by the equation $E ( y ) = \beta _ { 0 } + \beta _ { 1 } x + \beta _ { 2 } x ^ { 2 } + \beta _ { 3 } x ^ { 3 }$ .Which term provides a nonlinear component to the model enabling the line to reverse the direction of curvature?

What is stepwise regression,and when is it desirable to make use of this multiple regression technique?

What is the general idea of stepwise regression?

For the second-order polynomial model $E ( y ) = \beta _ { 0 } + \beta _ { 1 } x + \beta _ { 2 } x ^ { 2 }$ ,the shape of the curve will be determined by the relative sizes of $\beta _ { 1 }$ and $\beta _ { 2 }$ and on their signs.

The shape of the model described by the equation $E ( y ) = \beta _ { 0 } + \beta _ { 1 } x + \beta _ { 2 } x ^ { 2 }$ could be:

Discuss some of the signals for the presence of multicollinearity.

Three predictor variables are being considered for use in a linear regression model.Given the correlation matrix below,does it appear that multicollinearity could be a problem? x1 x3 x1 1.000 x2 0.025 1.000 0.968 0.897 1.000

In explaining students' test scores,which of the following independent variables would not best be represented by a dummy variable?

Multicollinearity is a situation in which the dependent variable is highly correlated with two or more of the independent variables in a multiple regression.

The regression model $\hat { Y }$ = 160 + 8x₁ - 5x₂ has been fitted to a set of data.If x₂ = 10,what will be the effect on $\hat { Y }$ if x₁ increases by 1 unit? $\hat { Y }$ will by

The model $\hat{ Y }$ = b₀ + b₁x₁ + b₂x₂ is referred to as the:

How do we test the reliability of a model?

The model $\hat { Y }$ = $b _ { 0 } x _ { 1 } ^ { b } 1 x _ { 2 } ^ { b _ { 2 } }$ is referred to as a multiplicative model with two predictor variables.

Which of the following statements are important steps in selecting a model?

A Preview of Business Statistics

Visual Description of Data

Statistical Description of Data

Data Collection and Sampling Methods

Probability: Review of Basic Concepts

Discrete Probability Distributions

Continuous Probability Distributions

Sampling Distributions

Estimation From Sample Data

Hypothesis Tests Involving a Sample Mean or Proportion

Hypothesis Tests Involving Two Sample Means

Analysis of Variance Tests

Chi-Square Applications

Nonparametric Methods

Simple Linear Regression and Correlation

Multiple Regression and Correlation

Models for Time Series and Forecasting

Decision Theory

Total Quality Management

Filters

Exam 17: Model Building

The first-order polynomial model is the same as the simple linear regression model.

Write a formula for the fourth-order polynomial model.Would such a polynomial model tend to be practical for use with business data?

If level of education has four possible categories,four qualitative variables would be needed to represent education in the regression model.

Briefly discuss the best subset regression approach.

What is stepwise regression,and when is it desirable to make use of this multiple regression technique?

What is the general idea of stepwise regression?

For the second-order polynomial model E(y)=β0+β1x+β2x2E ( y ) = \beta _ { 0 } + \beta _ { 1 } x + \beta _ { 2 } x ^ { 2 }E(y)=β0​+β1​x+β2​x2 ,the shape of the curve will be determined by the relative sizes of β1\beta _ { 1 }β1​ and β2\beta _ { 2 }β2​ and on their signs.

The shape of the model described by the equation E(y)=β0+β1x+β2x2E ( y ) = \beta _ { 0 } + \beta _ { 1 } x + \beta _ { 2 } x ^ { 2 }E(y)=β0​+β1​x+β2​x2 could be:

Discuss some of the signals for the presence of multicollinearity.

Three predictor variables are being considered for use in a linear regression model.Given the correlation matrix below,does it appear that multicollinearity could be a problem? x1 x3 x1 1.000 x2 0.025 1.000 0.968 0.897 1.000

In explaining students' test scores,which of the following independent variables would not best be represented by a dummy variable?

Multicollinearity is a situation in which the dependent variable is highly correlated with two or more of the independent variables in a multiple regression.

The regression model Y^\hat { Y }Y^ = 160 + 8x1 - 5x2 has been fitted to a set of data.If x2 = 10,what will be the effect on Y^\hat { Y }Y^ if x1 increases by 1 unit? Y^\hat { Y }Y^ will ____________________ by ____________________

The model Y^\hat{ Y }Y^ = b0 + b1x1 + b2x2 is referred to as the:

How do we test the reliability of a model?

The model Y^\hat { Y }Y^ = b0x1b1x2b2b _ { 0 } x _ { 1 } ^ { b } 1 x _ { 2 } ^ { b _ { 2 } }b0​x1b​1x2b2​​ is referred to as a multiplicative model with two predictor variables.

Which of the following statements are important steps in selecting a model?

A Preview of Business Statistics

Visual Description of Data

Statistical Description of Data

Data Collection and Sampling Methods

Probability: Review of Basic Concepts

Discrete Probability Distributions

Continuous Probability Distributions

Sampling Distributions

Estimation From Sample Data

Hypothesis Tests Involving a Sample Mean or Proportion

Hypothesis Tests Involving Two Sample Means

Analysis of Variance Tests

Chi-Square Applications

Nonparametric Methods

Simple Linear Regression and Correlation

Multiple Regression and Correlation

Models for Time Series and Forecasting

Decision Theory

Total Quality Management

Filters

For the second-order polynomial model $E ( y ) = \beta _ { 0 } + \beta _ { 1 } x + \beta _ { 2 } x ^ { 2 }$ ,the shape of the curve will be determined by the relative sizes of $\beta _ { 1 }$ and $\beta _ { 2 }$ and on their signs.

The shape of the model described by the equation $E ( y ) = \beta _ { 0 } + \beta _ { 1 } x + \beta _ { 2 } x ^ { 2 }$ could be:

The regression model $\hat { Y }$ = 160 + 8x₁ - 5x₂ has been fitted to a set of data.If x₂ = 10,what will be the effect on $\hat { Y }$ if x₁ increases by 1 unit? $\hat { Y }$ will by

The model $\hat{ Y }$ = b₀ + b₁x₁ + b₂x₂ is referred to as the:

The model $\hat { Y }$ = $b _ { 0 } x _ { 1 } ^ { b } 1 x _ { 2 } ^ { b _ { 2 } }$ is referred to as a multiplicative model with two predictor variables.