Deck 14: Building Multiple Regression Models
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Deck 14: Building Multiple Regression Models
1
A qualitative variable which represents categories such as geographical territories or job classifications may be included in a regression model by using indicator or dummy variables.
True
2
If each pair of independent variables is weakly correlated,there is no problem of multicollinearity.
False
3
A linear regression model cannot be used to explore the possibility that a quadratic relationship may exist between two variables.
False
4
If a square-transformation is applied to a series of positive numbers,all greater than 1,the numerical values of the numbers in the transformed series will be smaller than the corresponding numbers in the original series.
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5
Recoding data cannot improve the fit of a regression model.
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6
If a qualitative variable has c categories,then only (c - 1)dummy variables must be included in the regression model.
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7
A logarithmic transformation may be applied to both positive and negative numbers.
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8
If a qualitative variable has c categories,then c dummy variables must be included in the regression model,one for each category.
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9
Regression models in which the highest power of any predictor variable is 1 and in which there are no cross product terms are referred to as first-order models.
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10
Stepwise regression is one of the ways to prevent the problem of multicollinearity.
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11
If two or more independent variables are highly correlated,the regression analysis might suffer from the problem of singular collinearity.
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12
A linear regression model can be used to explore the possibility that a quadratic relationship may exist between two variables by suitably transforming the independent variable.
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13
The regression model y = 0 + 1 x1 + 2 x21 + is called a quadratic model.
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14
If a data set contains k independent variables,the "all possible regression" search procedure will determine 2k - 1 different models.
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15
If a data set contains k independent variables,the "all possible regression" search procedure will determine 2k different models.
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16
If the effect of an independent variable (e.g.,square footage)on a dependent variable (e.g.,price)is affected by different ranges of values for a second independent variable (e.g.,age ),the two independent variables are said to interact.
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17
Qualitative data can be incorporated into linear regression models using indicator variables.
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18
The interaction between two independent variables can be examined by including a new variable,which is the sum of the two independent variables,in the regression model.
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19
The regression model y = 0 + 1 x1 + 2 x2 + 3 x1x2 + is a first order model.
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20
The regression model y = 0 + 1 x1 + 2 x2 + 3 x3 + is a third order model.
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21
The following scatter plot indicates that _________. 
A) a log x transform may be useful
B) a log y transform may be useful
C) an x2 transform may be useful
D) no transform is needed
E) a (- x) transform may be useful

A) a log x transform may be useful
B) a log y transform may be useful
C) an x2 transform may be useful
D) no transform is needed
E) a (- x) transform may be useful
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22
A multiple regression analysis produced the following tables.
Using = 0.10 to test the null hypothesis H0: 2 = 0,the critical t value is ____.
A) ± 1.316
B) ± 1.314
C) ± 1.703
D) ± 1.780
E) ± 1.708


Using = 0.10 to test the null hypothesis H0: 2 = 0,the critical t value is ____.
A) ± 1.316
B) ± 1.314
C) ± 1.703
D) ± 1.780
E) ± 1.708
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23
The following scatter plot indicates that _________. 
A) a log x transform may be useful
B) a log y transform may be useful
C) a x2 transform may be useful
D) no transform is needed
E) a 1/x transform may be useful

A) a log x transform may be useful
B) a log y transform may be useful
C) a x2 transform may be useful
D) no transform is needed
E) a 1/x transform may be useful
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24
A multiple regression analysis produced the following tables.
For x1= 10,the predicted value of y is ____________.
A) 8.88.
B) 2,031.38
C) 2,53.86
D) 262.19
E) 2,535.86


A) 8.88.
B) 2,031.38
C) 2,53.86
D) 262.19
E) 2,535.86
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25
A local parent group was concerned with the increasing school cost for families with school aged children.The parent group was interested in understanding the relationship between the
The academic grade level for the child and the total costs spent per child per academic year.They
Performed a multiple regression analysis using total cost as the dependent variable and academic
Year (x1)as the independent variables.The multiple regression analysis produced the following
Tables.
Using = 0.05 to test the null hypothesis H0: 2 = 0,the critical t value is ____.
A) ± 1.311
B) ± 1.699
C) ± 1.703
D) ± 2.052
E) ± 2.502
The academic grade level for the child and the total costs spent per child per academic year.They
Performed a multiple regression analysis using total cost as the dependent variable and academic
Year (x1)as the independent variables.The multiple regression analysis produced the following
Tables.


Using = 0.05 to test the null hypothesis H0: 2 = 0,the critical t value is ____.
A) ± 1.311
B) ± 1.699
C) ± 1.703
D) ± 2.052
E) ± 2.502
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26
A local parent group was concerned with the increasing school cost for families with school aged children.The parent group was interested in understanding the relationship between the
The academic grade level for the child and the total costs spent per child per academic year.They
Performed a multiple regression analysis using total cost as the dependent variable and academic
Year (x1)as the independent variables.The multiple regression analysis produced the following
Tables.
Using = 0.01 to test the null hypothesis H0: 1 = 2 = 0,the critical F value is ____.
A) 5.42
B) 5.49
C) 7.60
D) 3.35
E) 2.49
The academic grade level for the child and the total costs spent per child per academic year.They
Performed a multiple regression analysis using total cost as the dependent variable and academic
Year (x1)as the independent variables.The multiple regression analysis produced the following
Tables.


Using = 0.01 to test the null hypothesis H0: 1 = 2 = 0,the critical F value is ____.
A) 5.42
B) 5.49
C) 7.60
D) 3.35
E) 2.49
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27
A multiple regression analysis produced the following tables.
For x1= 20,the predicted value of y is ____________.
A) 5,204.18.
B) 2,031.38
C) 2,538.86
D) 6262.19
E) 6,535.86


A) 5,204.18.
B) 2,031.38
C) 2,538.86
D) 6262.19
E) 6,535.86
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28
A multiple regression analysis produced the following tables.
Using = 0.10 to test the null hypothesis H0: 1 = 0,the critical t value is ____.
A) ± 1.316
B) ± 1.314
C) ± 1.703
D) ± 1.780
E) ± 1.708


Using = 0.10 to test the null hypothesis H0: 1 = 0,the critical t value is ____.
A) ± 1.316
B) ± 1.314
C) ± 1.703
D) ± 1.780
E) ± 1.708
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29
Multiple linear regression models can handle certain nonlinear relationships by ________.
A) biasing the sample
B) recoding or transforming variables
C) adjusting the resultant ANOVA table
D) adjusting the observed t and F values
E) performing nonlinear regression
A) biasing the sample
B) recoding or transforming variables
C) adjusting the resultant ANOVA table
D) adjusting the observed t and F values
E) performing nonlinear regression
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30
The logistic regression model constrains the estimated probabilities to lie between 0 and 100.
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31
The following scatter plot indicates that _________. 
A) a x2 transform may be useful
B) a log y transform may be useful
C) a x4 transform may be useful
D) no transform is needed
E) a x3 transform may be useful

A) a x2 transform may be useful
B) a log y transform may be useful
C) a x4 transform may be useful
D) no transform is needed
E) a x3 transform may be useful
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32
A local parent group was concerned with the increasing school cost for families with school aged children.The parent group was interested in understanding the relationship between the
The academic grade level for the child and the total costs spent per child per academic year.They
Performed a multiple regression analysis using total cost as the dependent variable and academic
Year (x1)as the independent variables.The multiple regression analysis produced the following
Tables.
The regression equation for this analysis is ____________.
A) y = 707.9144 + 2.903307 x1 + 11.91297 x12
B) y = 707.9144 + 435.1183 x1 + 1.626947 x12
C) y = 435.1183 + 81.62802 x1 + 3.806211 x12
D) y = 1.626947 + 0.035568 x1 + 3.129878 x12
E) y = 1.626947 + 0.035568 x1 - 3.129878 x12
The academic grade level for the child and the total costs spent per child per academic year.They
Performed a multiple regression analysis using total cost as the dependent variable and academic
Year (x1)as the independent variables.The multiple regression analysis produced the following
Tables.


A) y = 707.9144 + 2.903307 x1 + 11.91297 x12
B) y = 707.9144 + 435.1183 x1 + 1.626947 x12
C) y = 435.1183 + 81.62802 x1 + 3.806211 x12
D) y = 1.626947 + 0.035568 x1 + 3.129878 x12
E) y = 1.626947 + 0.035568 x1 - 3.129878 x12
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33
A multiple regression analysis produced the following tables.
The sample size for this analysis is ____________.
A) 28
B) 25
C) 30
D) 27
E) 2


A) 28
B) 25
C) 30
D) 27
E) 2
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34
A local parent group was concerned with the increasing school cost for families with school aged children.The parent group was interested in understanding the relationship between the
The academic grade level for the child and the total costs spent per child per academic year.They
Performed a multiple regression analysis using total cost as the dependent variable and academic
Year (x1)as the independent variables.The multiple regression analysis produced the following
Tables.
The sample size for this analysis is ____________.
A) 27
B) 29
C) 30
D) 25
E) 28
The academic grade level for the child and the total costs spent per child per academic year.They
Performed a multiple regression analysis using total cost as the dependent variable and academic
Year (x1)as the independent variables.The multiple regression analysis produced the following
Tables.


A) 27
B) 29
C) 30
D) 25
E) 28
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35
We may use logistic regression when the dependent variable is a dummy variable,coded 0 or 1.
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36
A local parent group was concerned with the increasing school cost for families with school aged children.The parent group was interested in understanding the relationship between the
The academic grade level for the child and the total costs spent per child per academic year.They
Performed a multiple regression analysis using total cost as the dependent variable and academic
Year (x1)as the independent variables.The multiple regression analysis produced the following
Tables.

Using = 0.05 to test the null hypothesis H0: 1 = 0,the critical t value is ____.
A) ± 1.311
B) ± 1.699
C) ± 1.703
D) ± 2.502
E) ± 2.052
The academic grade level for the child and the total costs spent per child per academic year.They
Performed a multiple regression analysis using total cost as the dependent variable and academic
Year (x1)as the independent variables.The multiple regression analysis produced the following
Tables.


Using = 0.05 to test the null hypothesis H0: 1 = 0,the critical t value is ____.
A) ± 1.311
B) ± 1.699
C) ± 1.703
D) ± 2.502
E) ± 2.052
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37
A multiple regression analysis produced the following tables.
Using = 0.05 to test the null hypothesis H0: 1 = 2 = 0,the critical F value is ____.
A) 4.24
B) 3.39
C) 5.57
D) 3.35
E) 2.35


A) 4.24
B) 3.39
C) 5.57
D) 3.35
E) 2.35
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38
A multiple regression analysis produced the following tables.
The regression equation for this analysis is ____________.
A) y = 762.1533 + 96.8433 x1 + 3.007943 x12
B) y = 1411.876 + 762.1533 x1 + 1.852483 x12
C) y = 1411.876 + 35.18215 x1 + 7.721648 x12
D) y = 762.1533 + 1.852483 x1 + 0.074919 x12
E) y = 762.1533 - 1.852483 x1 + 0.074919 x12


A) y = 762.1533 + 96.8433 x1 + 3.007943 x12
B) y = 1411.876 + 762.1533 x1 + 1.852483 x12
C) y = 1411.876 + 35.18215 x1 + 7.721648 x12
D) y = 762.1533 + 1.852483 x1 + 0.074919 x12
E) y = 762.1533 - 1.852483 x1 + 0.074919 x12
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39
If the variance inflation factor is bigger than 10,the regression analysis might suffer from the problem of multicollinearity.
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40
The following scatter plot indicates that _________. 
A) a log x transform may be useful
B) a y2 transform may be useful
C) a x2 transform may be useful
D) no transform is needed
E) a 1/x transform may be useful

A) a log x transform may be useful
B) a y2 transform may be useful
C) a x2 transform may be useful
D) no transform is needed
E) a 1/x transform may be useful
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41
A local parent group was concerned with the increasing school cost for families with school aged children.The parent group was interested in understanding the relationship between the
The academic grade level for the child and the total costs spent per child per academic year.They
Performed a multiple regression analysis using total cost as the dependent variable and academic
Year (x1)as the independent variables.The multiple regression analysis produced the following
Tables.
For a child in grade 5 (x1= 2),the predicted value of y is ____________.
A) 707.91
B) 1,020.26
C) 781.99
D) 840.06
E) 1078.32
The academic grade level for the child and the total costs spent per child per academic year.They
Performed a multiple regression analysis using total cost as the dependent variable and academic
Year (x1)as the independent variables.The multiple regression analysis produced the following
Tables.


A) 707.91
B) 1,020.26
C) 781.99
D) 840.06
E) 1078.32
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42
A local parent group was concerned with the increasing school cost for families with school aged children.The parent group was interested in understanding the relationship between the
The academic grade level for the child and the total costs spent per child per academic year.They
Performed a multiple regression analysis using total cost as the dependent variable and academic
Year (x1)as the independent variables.The multiple regression analysis produced the following
Tables.
For a child in grade 10 (x1= 10)the predicted value of y is ____________.
A) 707.91
B) 1,117.38
C) 856.08
D) 2,189.54
E) 1,928.24
The academic grade level for the child and the total costs spent per child per academic year.They
Performed a multiple regression analysis using total cost as the dependent variable and academic
Year (x1)as the independent variables.The multiple regression analysis produced the following
Tables.


A) 707.91
B) 1,117.38
C) 856.08
D) 2,189.54
E) 1,928.24
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43
Abby Kratz,a market specialist at the market research firm of Saez,Sikes,and Spitz,is analyzing household budget data collected by her firm. Abby's dependent variable is weekly household expenditures on groceries (in $'s),and her independent variables are annual household income (in $1,000's)and household neighborhood (0 = suburban,1 = rural). Regression analysis of the data yielded the following table.
For two households,one suburban and one rural,Abby's model predicts ________.
A) equal weekly expenditures for groceries
B) the suburban household's weekly expenditures for groceries will be $49 more
C) the rural household's weekly expenditures for groceries will be $49 more
D) the suburban household's weekly expenditures for groceries will be $8 more
E) the rural household's weekly expenditures for groceries will be $49 less

A) equal weekly expenditures for groceries
B) the suburban household's weekly expenditures for groceries will be $49 more
C) the rural household's weekly expenditures for groceries will be $49 more
D) the suburban household's weekly expenditures for groceries will be $8 more
E) the rural household's weekly expenditures for groceries will be $49 less
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44
Yvonne Yang,VP of Finance at Discrete Components,Inc.(DCI),wants a regression model which predicts the average collection period on credit sales. Her data set includes two qualitative variables: sales discount rates (0%,2%,4%,and 6%),and total assets of credit customers (small,medium,and large).The number of dummy variables needed for "sales discount rate" in Yvonne's regression model is ________.
A) 1
B) 2
C) 3
D) 4
E) 7
A) 1
B) 2
C) 3
D) 4
E) 7
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45
Alan Bissell,a market analyst for City Sound Online Mart,is analyzing sales from heavy metal song downloads.Alan's dependent variable is annual heavy metal song download sales (in $1,000,000's),and his independent variables are website visitors (in 1,000's)and type of download format requested (0 = MP3,1 = other).Regression analysis of the data yielded the following tables.
For an MP3 sales with 10,000 website visitors,Alan's model predicts annual sales of heavy metal dong downloads of ________________.
A) $2,100,000
B) $524,507
C) $533,333
D) $729,683
E) $21,000,000

A) $2,100,000
B) $524,507
C) $533,333
D) $729,683
E) $21,000,000
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46
Hope Hernandez is the new regional Vice President for a large gasoline station chain.She wants a regression model to predict sales in the convenience stores. Her data set includes two qualitative variables: the gasoline station location (inner city,freeway,and suburbs),and curb appeal of the convenience store (low,medium,and high).The number of dummy variables needed for "curb appeal" in Hope's regression model is ______.
A) 1
B) 2
C) 3
D) 4
E) 5
A) 1
B) 2
C) 3
D) 4
E) 5
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47
Abby Kratz,a market specialist at the market research firm of Saez,Sikes,and Spitz,is analyzing household budget data collected by her firm. Abby's dependent variable is weekly household expenditures on groceries (in $'s),and her independent variables are annual household income (in $1,000's)and household neighborhood (0 = suburban,1 = rural). Regression analysis of the data yielded the following table.
Abby's model is ________________.
A) y = 19.68247 + 10.01176 x1 + 1.965934 x2
B) y = 1.965934 + 9.940612 x1 + 6.416667 x2
C) y = 10.01176 + 0.174564 x1 + 7.655776 x2
D) y = 19.68247 - 1.735272 x1 + 49.12456 x2
E) y = 19.68247 + 1.735272 x1 + 49.12456 x2

A) y = 19.68247 + 10.01176 x1 + 1.965934 x2
B) y = 1.965934 + 9.940612 x1 + 6.416667 x2
C) y = 10.01176 + 0.174564 x1 + 7.655776 x2
D) y = 19.68247 - 1.735272 x1 + 49.12456 x2
E) y = 19.68247 + 1.735272 x1 + 49.12456 x2
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48
In multiple regression analysis,qualitative variables are sometimes referred to as ___.
A) dummy variables
B) quantitative variables
C) dependent variables
D) performance variables
E) cardinal variables
A) dummy variables
B) quantitative variables
C) dependent variables
D) performance variables
E) cardinal variables
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49
Which of the following iterative search procedures for model-building in a multiple regression analysis reevaluates the contribution of variables previously include in the model after entering a new independent variable?
A) Backward elimination
B) Stepwise regression
C) Forward selection
D) All possible regressions
E) Backward selection
A) Backward elimination
B) Stepwise regression
C) Forward selection
D) All possible regressions
E) Backward selection
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50
Abby Kratz,a market specialist at the market research firm of Saez,Sikes,and Spitz,is analyzing household budget data collected by her firm. Abby's dependent variable is weekly household expenditures on groceries (in $'s),and her independent variables are annual household income (in $1,000's)and household neighborhood (0 = suburban,1 = rural). Regression analysis of the data yielded the following table.
For a suburban household with $90,000 annual income,Abby's model predicts weekly grocery expenditure of ________________.
A) $156.19
B) $224.98
C) $444.62
D) $141.36
E) $175.86

A) $156.19
B) $224.98
C) $444.62
D) $141.36
E) $175.86
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51
Which of the following iterative search procedures for model-building in a multiple regression analysis starts with all independent variables in the model and then drops non-significant independent variables is a step-by-step manner?
A) Backward elimination
B) Stepwise regression
C) Forward selection
D) All possible regressions
E) Backward selection
A) Backward elimination
B) Stepwise regression
C) Forward selection
D) All possible regressions
E) Backward selection
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52
Alan Bissell,a market analyst for City Sound Online Mart,is analyzing sales from heavy metal song downloads.Alan's dependent variable is annual heavy metal song download sales (in $1,000,000's),and his independent variables are website visitors (in 1,000's)and type of download format requested (0 = MP3,1 = other).Regression analysis of the data yielded the following tables.
Alan's model is ________________.
A) y = 1.7 + 0.384212 x1 + 4.424638 x2 + 0.00166 x3
B) y = 1.7 + 0.04 x1 + 1.5666667 x2
C) y = 0.384212 + 0.014029 x1 + 0.20518 x2
D) y = 4.424638 + 2.851146 x1 - 7.63558 x2
E) y = 1.7 + 0.04 x1 - 1.5666667 x2

A) y = 1.7 + 0.384212 x1 + 4.424638 x2 + 0.00166 x3
B) y = 1.7 + 0.04 x1 + 1.5666667 x2
C) y = 0.384212 + 0.014029 x1 + 0.20518 x2
D) y = 4.424638 + 2.851146 x1 - 7.63558 x2
E) y = 1.7 + 0.04 x1 - 1.5666667 x2
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53
If a qualitative variable has 4 categories,how many dummy variables must be created and used in the regression analysis?
A) 3
B) 4
C) 5
D) 6
E) 7
A) 3
B) 4
C) 5
D) 6
E) 7
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54
Yvonne Yang,VP of Finance at Discrete Components,Inc.(DCI),wants a regression model which predicts the average collection period on credit sales. Her data set includes two qualitative variables: sales discount rates (0%,2%,4%,and 6%),and total assets of credit customers (small,medium,and large).The number of dummy variables needed for "total assets of credit customer" in Yvonne's regression model is ________.
A) 1
B) 2
C) 3
D) 4
E) 7
A) 1
B) 2
C) 3
D) 4
E) 7
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55
Alan Bissell,a market analyst for City Sound Online Mart,is analyzing sales from heavy metal song downloads.Alan's dependent variable is annual heavy metal song download sales (in $1,000,000's),and his independent variables are website visitors (in 1,000's)and type of download format requested (0 = MP3,1 = other).Regression analysis of the data yielded the following tables.
For the same number of website visitors,what is difference between the predicted sales for MP3 versus 'other' heavy metal song downloads
A) $1,566,666 higher sales for 'other' formats
B) the same sales for both formats
C) $1,566,666 lower sales for the 'other' format
D) $1,700,000 higher sales for the MP3 format
E) $ 1,700,000 lower sales for the 'other' format

A) $1,566,666 higher sales for 'other' formats
B) the same sales for both formats
C) $1,566,666 lower sales for the 'other' format
D) $1,700,000 higher sales for the MP3 format
E) $ 1,700,000 lower sales for the 'other' format
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k this deck
56
Abby Kratz,a market specialist at the market research firm of Saez,Sikes,and Spitz,is analyzing household budget data collected by her firm. Abby's dependent variable is weekly household expenditures on groceries (in $'s),and her independent variables are annual household income (in $1,000's)and household neighborhood (0 = suburban,1 = rural). Regression analysis of the data yielded the following table.
For a rural household with $90,000 annual income,Abby's model predicts weekly grocery expenditure of ________________.
A) $156.19
B) $224.98
C) $444.62
D) $141.36
E) $175.86

A) $156.19
B) $224.98
C) $444.62
D) $141.36
E) $175.86
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Unlock Deck
k this deck
57
After a transformation of the y-variable values into log y,and performing a regression analysis produced the following tables.
For x1= 10,the predicted value of y is ____________.
A) 155.79
B) 1.25
C) 2.42
D) 189.06
E) 18.90


A) 155.79
B) 1.25
C) 2.42
D) 189.06
E) 18.90
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Unlock for access to all 95 flashcards in this deck.
Unlock Deck
k this deck
58
Alan Bissell,a market analyst for City Sound Online Mart,is analyzing sales from heavy metal song downloads.Alan's dependent variable is annual heavy metal song download sales (in $1,000,000's),and his independent variables are website visitors (in 1,000's)and type of download format requested (0 = MP3,1 = other).Regression analysis of the data yielded the following tables.
For a 'other' download formats with 10,000 website visitors,Alan's model predicts annual sales of heavy metal song downloads of ________________.
A) $2,100,000
B) $524,507
C) $533,333
D) $729,683
E) $210,000

A) $2,100,000
B) $524,507
C) $533,333
D) $729,683
E) $210,000
Unlock Deck
Unlock for access to all 95 flashcards in this deck.
Unlock Deck
k this deck
59
Hope Hernandez is the new regional Vice President for a large gasoline station chain.She wants a regression model to predict sales in the convenience stores. Her data set includes two qualitative variables: the gasoline station location (inner city,freeway,and suburbs),and curb appeal of the convenience store (low,medium,and high).The number of dummy variables needed for Hope's regression model is ______.
A) 2
B) 4
C) 6
D) 8
E) 9
A) 2
B) 4
C) 6
D) 8
E) 9
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Unlock for access to all 95 flashcards in this deck.
Unlock Deck
k this deck
60
A local parent group was concerned with the increasing school cost for families with school aged children.The parent group was interested in understanding the relationship between the
The academic grade level for the child and the total costs spent per child per academic year.They
Performed a multiple regression analysis using total cost as the dependent variable and academic
Year (x1)as the independent variables.The multiple regression analysis produced the following
Tables.
These results indicate that ____________.
A) none of the predictor variables is significant at the 5% level
B) each predictor variable is significant at the 5% level
C) x1 is the only predictor variable significant at the 5% level
D) x12 is the only predictor variable significant at the 5% level
E) each predictor variable is insignificant at the 5% level
The academic grade level for the child and the total costs spent per child per academic year.They
Performed a multiple regression analysis using total cost as the dependent variable and academic
Year (x1)as the independent variables.The multiple regression analysis produced the following
Tables.


A) none of the predictor variables is significant at the 5% level
B) each predictor variable is significant at the 5% level
C) x1 is the only predictor variable significant at the 5% level
D) x12 is the only predictor variable significant at the 5% level
E) each predictor variable is insignificant at the 5% level
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Unlock for access to all 95 flashcards in this deck.
Unlock Deck
k this deck
61
A research project was conducted to study the effect of smoking and weight upon resting pulse rate.The response variable is coded as 1 when the pulse rate is low and 0 when it high.Smoking is also coding as 1 when smoking and 0 when not smoking.Shown below is Minitab output from a logistic regression. Response Information
Variable Value Count
Rating Pulse 1 70 (Event)
0 22
Total 92
Logistic Regression Table
Odds 95% CI
Predictor Coef SE Coef Z P Ratio Lower Upper
Constant -1.98717 1.67930 -1.18 0.237
Weight 0.0250226 0.0122551 2.04 0.041 1.03 1.00 1.05
Smokes -1.19297 0.552980 -2.16 0.031 0.30 0.10 0.90
Log-Likelihood = -46.820
Test that all slopes are zero: G = 7.574,DF = 2,P-Value = 0.023
The log of the odds ratio or logit equation is:
A) log(S)=-1.19297+0.0250226 Weight-1.98717 Smokes
B) S=-1.98717+0.025226 Weight-1.19297 Smokes
C) Rating Pulse=-1.98717+0.025226 Weight-1.19297 Smokes
D) log(S) =-1.98717+0.025226 Weight-1.19297 Smokes
E) log(p)=-1.98717+0.025226 Weight-1.19297 Smokes
Variable Value Count
Rating Pulse 1 70 (Event)
0 22
Total 92
Logistic Regression Table
Odds 95% CI
Predictor Coef SE Coef Z P Ratio Lower Upper
Constant -1.98717 1.67930 -1.18 0.237
Weight 0.0250226 0.0122551 2.04 0.041 1.03 1.00 1.05
Smokes -1.19297 0.552980 -2.16 0.031 0.30 0.10 0.90
Log-Likelihood = -46.820
Test that all slopes are zero: G = 7.574,DF = 2,P-Value = 0.023
The log of the odds ratio or logit equation is:
A) log(S)=-1.19297+0.0250226 Weight-1.98717 Smokes
B) S=-1.98717+0.025226 Weight-1.19297 Smokes
C) Rating Pulse=-1.98717+0.025226 Weight-1.19297 Smokes
D) log(S) =-1.98717+0.025226 Weight-1.19297 Smokes
E) log(p)=-1.98717+0.025226 Weight-1.19297 Smokes
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62
An "all possible regressions" search of a data set containing "k" independent variables will produce __________ regressions.
A) 2k -1
B) 2k - 1
C) k2 - 1
D) 2k - 1
E) 2k
A) 2k -1
B) 2k - 1
C) k2 - 1
D) 2k - 1
E) 2k
Unlock Deck
Unlock for access to all 95 flashcards in this deck.
Unlock Deck
k this deck
63
Inspection of the following table of correlation coefficients for variables in a multiple regression analysis reveals that the first independent variable that will be entered into the regression model by the forward selection procedure will be ___________. 
A) x1
B) x2
C) x3
D) x4
E) x5

A) x1
B) x2
C) x3
D) x4
E) x5
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Unlock Deck
k this deck
64
Inspection of the following table of correlation coefficients for variables in a multiple regression analysis reveals potential multicollinearity with variables ___________. 
A) x1 and x2
B) x1 and x4
C) x4 and x5
D) x4 and x3
E) x5 and y

A) x1 and x2
B) x1 and x4
C) x4 and x5
D) x4 and x3
E) x5 and y
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Unlock for access to all 95 flashcards in this deck.
Unlock Deck
k this deck
65
Carlos Cavazos,Director of Human Resources,is exploring employee absenteeism at the Plano Piano Plant.A multiple regression analysis was performed using the following variables.The results are presented below.
Which of the following conclusions can be drawn from the above results?
A) All the independent variables in the regression are significant at 5% level.
B) Commuting distance is a highly significant (<1%) variable in explaining absenteeism.
C) Age of the employees tends to have a very significant (<1%) effect on absenteeism.
D) This model explains a little over 49% of the variability in absenteeism data.
E) A single-parent household employee is expected to be absent less number of days all other variables held constant compared to one who is not a single-parent household.




A) All the independent variables in the regression are significant at 5% level.
B) Commuting distance is a highly significant (<1%) variable in explaining absenteeism.
C) Age of the employees tends to have a very significant (<1%) effect on absenteeism.
D) This model explains a little over 49% of the variability in absenteeism data.
E) A single-parent household employee is expected to be absent less number of days all other variables held constant compared to one who is not a single-parent household.
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66
Inspection of the following table of correlation coefficients for variables in a multiple regression analysis reveals that the first independent variable entered by the forward selection procedure will be ___________. 
A) x2
B) x3
C) x4
D) x5
E) x1

A) x2
B) x3
C) x4
D) x5
E) x1
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Unlock for access to all 95 flashcards in this deck.
Unlock Deck
k this deck
67
Inspection of the following table of correlation coefficients for variables in a multiple regression analysis reveals potential multicollinearity with variables ___________. 
A) x1 and x2
B) x1 and x5
C) x3 and x4
D) x2 and x5
E) x3 and x5

A) x1 and x2
B) x1 and x5
C) x3 and x4
D) x2 and x5
E) x3 and x5
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Unlock for access to all 95 flashcards in this deck.
Unlock Deck
k this deck
68
Inspection of the following table of correlation coefficients for variables in a multiple regression analysis reveals that the first independent variable entered by the forward selection procedure will be ___________. 
A) x1
B) x2
C) x3
D) x4
E) x5

A) x1
B) x2
C) x3
D) x4
E) x5
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Unlock for access to all 95 flashcards in this deck.
Unlock Deck
k this deck
69
An "all possible regressions" search of a data set containing 7 independent variables will produce ______ regressions.
A) 13
B) 127
C) 48
D) 64
E) 97
A) 13
B) 127
C) 48
D) 64
E) 97
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Unlock Deck
k this deck
70
An acceptable method of managing multicollinearity in a regression model is the ___.
A) use the forward selection procedure
B) use the backward elimination procedure
C) use the forward elimination procedure
D) use the stepwise regression procedure
E) use all possible regressions
A) use the forward selection procedure
B) use the backward elimination procedure
C) use the forward elimination procedure
D) use the stepwise regression procedure
E) use all possible regressions
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Unlock Deck
k this deck
71
An "all possible regressions" search of a data set containing 8 independent variables will produce ______ regressions.
A) 8
B) 15
C) 256
D) 64
E) 255
A) 8
B) 15
C) 256
D) 64
E) 255
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Unlock for access to all 95 flashcards in this deck.
Unlock Deck
k this deck
72
Inspection of the following table of correlation coefficients for variables in a multiple regression analysis reveals that the first independent variable that will be entered into the regression model by the forward selection procedure will be ___________. 
A) x1
B) x2
C) x3
D) x4
E) x5

A) x1
B) x2
C) x3
D) x4
E) x5
Unlock Deck
Unlock for access to all 95 flashcards in this deck.
Unlock Deck
k this deck
73
Suppose a company is interested in understanding the effect of age and gender on the likelihood a customer will purchase a new product.The data analyst intends to run a logistic regression on her data.Which of the following variable(s)will the analyst need to code as 0 or 1 prior to performing the logistic regression analysis?
A) age and gender
B) age and purchase status
C) age
D) purchase status
E) gender and purchase status
A) age and gender
B) age and purchase status
C) age
D) purchase status
E) gender and purchase status
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Unlock for access to all 95 flashcards in this deck.
Unlock Deck
k this deck
74
An appropriate method to identify multicollinearity in a regression model is to ____.
A) examine a residual plot
B) examine the ANOVA table
C) examine a correlation matrix
D) examine the partial regression coefficients
E) examine the R2 of the regression model
A) examine a residual plot
B) examine the ANOVA table
C) examine a correlation matrix
D) examine the partial regression coefficients
E) examine the R2 of the regression model
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75
Large correlations between two or more independent variables in a multiple regression model could result in the problem of ________.
A) multicollinearity
B) autocorrelation
C) partial correlation
D) rank correlation
E) non-normality
A) multicollinearity
B) autocorrelation
C) partial correlation
D) rank correlation
E) non-normality
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k this deck
76
A multiple regression analysis produced the following tables.
The minimum value of the predicted value of the dependent variable is reached when
X1 = ______.
A) 2.15815
B) 3.18512
C) 3.37785
D) 3.40125
E) a value not listed here


X1 = ______.
A) 2.15815
B) 3.18512
C) 3.37785
D) 3.40125
E) a value not listed here
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k this deck
77
Inspection of the following table of correlation coefficients for variables in a multiple regression analysis reveals potential multicollinearity with variables ___________. 
A) x1 and x5
B) x2 and x3
C) x4 and x2
D) x4 and x3
E) x4 and y

A) x1 and x5
B) x2 and x3
C) x4 and x2
D) x4 and x3
E) x4 and y
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Unlock Deck
k this deck
78
An "all possible regressions" search of a data set containing 5 independent variables will produce ______ regressions.
A) 31
B) 10
C) 25
D) 32
E) 24
A) 31
B) 10
C) 25
D) 32
E) 24
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79
Which of the following iterative search procedures for model-building in a multiple regression analysis adds variables to model as it proceeds,but does not reevaluate the contribution of previously entered variables?
A) Backward elimination
B) Stepwise regression
C) Forward selection
D) All possible regressions
E) Forward elimination
A) Backward elimination
B) Stepwise regression
C) Forward selection
D) All possible regressions
E) Forward elimination
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80
A useful technique in controlling multicollinearity involves the _________.
A) use of variance inflation factors
B) use the backward elimination procedure
C) use the forward elimination procedure
D) use the forward selection procedure
E) use all possible regressions
A) use of variance inflation factors
B) use the backward elimination procedure
C) use the forward elimination procedure
D) use the forward selection procedure
E) use all possible regressions
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Unlock Deck
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