Question 1

Scatterplots are used for identifying outliers and quantifying relationships between variables.

Accepted Answer

A) True 
 B)False

Question 2

In choosing the "best-fitting" line through a set of points in linear regression,we choose the one with the:

Accepted Answer

A)   smallest sum of squared residuals
B)   largest sum of squared residuals
C)   smallest number of outliers
D)   largest number of points on the line
E)   None of these optionsF) A) and E)
G) B) and E)

Question 3

In a simple linear regression problem,suppose that $\sum e _ { i } ^ { 2 } = 12.48 \text { and } \sum \left( Y _ { i } - Y \right) ^ { 2 } = 124.8$ 
.Then the percentage of variation explained $R ^ { 2 }$ 
must be 0.90.

Accepted Answer

A) True 
 B)False

Question 4

In simple linear regression,the divisor of the standard error of estimate $S _ { e }$ 
is n - 1;simply because there is only one explanatory variable of interest.

Accepted Answer

A) True 
 B)False

Question 5

The regression line  Y^=3+2.5X\hat { Y } = 3 + 2.5 XY^=3+2.5X 
Has been fitted to the data points (28,60) , (20,50) , (10,18) ,and (25,55) .The sum of the squared residuals will be:

Accepted Answer

A)   20.25
B)   16.00
C)   49.00
D)   94.25 E) A) and B)
F) A) and C)

Question 6

The coefficients for logarithmically transformed explanatory variables should be interpreted as the percent change in the dependent variable for a 1% percent change in the explanatory variable.

Accepted Answer

A) True 
 B)False

Question 7

In multiple regression,the coefficients reflect the expected change in:

Accepted Answer

A)   Y when the associated X value increases by one unit
B)   X when the associated Y value increases by one unit
C)   Y when the associated X value decreases by one unit
D)   X when the associated Y value decreases by one unitE) A) and D)
F) B) and C)

Question 8

The term autocorrelation refers to:

Accepted Answer

A)   the analyzed data refers to itself
B)   the sample is related too closely to the population
C)   the data are in a loop (values repeat themselves) 
D)   time series variables are usually related to their own past valuesE) None of the above
F) A) and C)

Question 9

In regression analysis,which of the following causal relationships are possible?

Accepted Answer

A)   X causes Y to vary
B)   Y causes X to vary
C)   Other variables cause both X and Y to vary
D)   All of these optionsE) None of the above
F) A) and B)

Question 10

In regression analysis,we can often use the standard error of estimate $S _ { e }$ 
to judge which of several potential regression equations is the most useful.

Accepted Answer

A) True 
 B)False

Question 11

is/are especially helpful in identifying outliers.

Accepted Answer

A)   Linear regression
B)   Regression analysis
C)   Normal curves
D)   Scatterplots
E)   Multiple regressionF) All of the above
G) B) and E)

Question 12

Correlation is used to determine the strength of the linear relationship between an explanatory variable X and response variable Y.

Accepted Answer

A) True 
 B)False

Question 13

In linear regression,we can have an interaction variable.Algebraically,the interaction variable is the other variables in the regression equation.

Accepted Answer

A)   sum
B)   ratio
C)   product
D)   meanE) All of the above
F) C) and D)

Question 14

In a simple regression with a single explanatory variable,the multiple R is the same as the standard correlation between the Y variable and the explanatory X variable.

Accepted Answer

A) True 
 B)False

Question 15

When the scatterplot appears as a shapeless swarm of points,this can indicate that there is no relationship between the response variable Y and the explanatory variable X,or at least none worth pursuing.

Accepted Answer

A) True 
 B)False

Question 16

Outliers are observations that

Accepted Answer

A)   lie outside the sample
B)   render the study useless
C)   lie outside the typical pattern of points on a scatterplot
D)   disrupt the entire linear trendE) A) and D)
F) A) and C)

Question 17

The adjusted R2 is adjusted for the number of explanatory variables in a regression equation,and it has the same interpretation as the standard R2.

Accepted Answer

A) True 
 B)False

Question 18

In a multiple regression analysis with three explanatory variables,suppose that there are 60 observations and the sum of the residuals squared is 28.The standard error of estimate must be 0.7071.

Accepted Answer

A) True 
 B)False

Question 19

A logarithmic transformation of the response variable Y is often useful when the distribution of Y is symmetric.

Accepted Answer

A) True 
 B)False

Question 20

In the multiple regression model $\hat { Y } = 6.75 + 2.25 X _ { 1 } + 3.5 X _ { 2 }$ 
we interpret X1 as follows: holding X2 constant,if X1 increases by 1 unit,then the expected value of Y will increase by 9 units.

Accepted Answer

A) True 
 B)False

Exam 10: Regression Analysis: Estimating Relationships

The adjusted R2 is adjusted for the number of explanatory variables in a regression equation,and it has the same interpretation as the standard R2.

Correct AnswerverifiedShow Answer

A logarithmic transformation of the response variable Y is often useful when the distribution of Y is symmetric.

Correct AnswerverifiedShow Answer

In a simple linear regression problem,suppose that ∑ei2=12.48 and ∑(Yi−Y)2=124.8\sum e _ { i } ^ { 2 } = 12.48 \text { and } \sum \left( Y _ { i } - Y \right) ^ { 2 } = 124.8∑ei2​=12.48 and ∑(Yi​−Y)2=124.8 .Then the percentage of variation explained R2R ^ { 2 }R2 must be 0.90.

Correct AnswerverifiedShow Answer

In a simple regression with a single explanatory variable,the multiple R is the same as the standard correlation between the Y variable and the explanatory X variable.

Correct AnswerverifiedShow Answer

The regression line Y^=3+2.5X\hat { Y } = 3 + 2.5 XY^=3+2.5X Has been fitted to the data points (28,60) , (20,50) , (10,18) ,and (25,55) .The sum of the squared residuals will be:

Correct AnswerverifiedShow Answer

The term autocorrelation refers to:

Correct AnswerverifiedShow Answer

In regression analysis,we can often use the standard error of estimate SeS _ { e }Se​ to judge which of several potential regression equations is the most useful.

Correct AnswerverifiedShow Answer

is/are especially helpful in identifying outliers.

Correct AnswerverifiedShow Answer

When the scatterplot appears as a shapeless swarm of points,this can indicate that there is no relationship between the response variable Y and the explanatory variable X,or at least none worth pursuing.

Correct AnswerverifiedShow Answer

In multiple regression,the coefficients reflect the expected change in:

Correct AnswerverifiedShow Answer

Scatterplots are used for identifying outliers and quantifying relationships between variables.

Correct AnswerverifiedShow Answer

Outliers are observations that

Correct AnswerverifiedShow Answer

Correlation is used to determine the strength of the linear relationship between an explanatory variable X and response variable Y.

Correct AnswerverifiedShow Answer

In the multiple regression model Y^=6.75+2.25X1+3.5X2\hat { Y } = 6.75 + 2.25 X _ { 1 } + 3.5 X _ { 2 }Y^=6.75+2.25X1​+3.5X2​ we interpret X1 as follows: holding X2 constant,if X1 increases by 1 unit,then the expected value of Y will increase by 9 units.

Correct AnswerverifiedShow Answer

In regression analysis,which of the following causal relationships are possible?

Correct AnswerverifiedShow Answer

The coefficients for logarithmically transformed explanatory variables should be interpreted as the percent change in the dependent variable for a 1% percent change in the explanatory variable.

Correct AnswerverifiedShow Answer

In a multiple regression analysis with three explanatory variables,suppose that there are 60 observations and the sum of the residuals squared is 28.The standard error of estimate must be 0.7071.

Correct AnswerverifiedShow Answer

In simple linear regression,the divisor of the standard error of estimate SeS _ { e }Se​ is n - 1;simply because there is only one explanatory variable of interest.

Correct AnswerverifiedShow Answer

In linear regression,we can have an interaction variable.Algebraically,the interaction variable is the other variables in the regression equation.

Correct AnswerverifiedShow Answer

In choosing the "best-fitting" line through a set of points in linear regression,we choose the one with the:

Correct AnswerverifiedShow Answer

The adjusted R² is adjusted for the number of explanatory variables in a regression equation,and it has the same interpretation as the standard R².

Correct Answer
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Correct Answer
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In a simple linear regression problem,suppose that $\sum e _ { i } ^ { 2 } = 12.48 \text { and } \sum \left( Y _ { i } - Y \right) ^ { 2 } = 124.8$ .Then the percentage of variation explained $R ^ { 2 }$ must be 0.90.

Correct Answer
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Correct Answer
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The regression line $\hat { Y } = 3 + 2.5 X$ Has been fitted to the data points (28,60) , (20,50) , (10,18) ,and (25,55) .The sum of the squared residuals will be:

Correct Answer
verified

Correct Answer
verified

In regression analysis,we can often use the standard error of estimate $S _ { e }$ to judge which of several potential regression equations is the most useful.

Correct Answer
verified

Correct Answer
verified

Correct Answer
verified

Correct Answer
verified

Correct Answer
verified

Correct Answer
verified

Correct Answer
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In the multiple regression model $\hat { Y } = 6.75 + 2.25 X _ { 1 } + 3.5 X _ { 2 }$ we interpret X₁ as follows: holding X₂ constant,if X₁ increases by 1 unit,then the expected value of Y will increase by 9 units.

Correct Answer
verified

Correct Answer
verified

Correct Answer
verified

Correct Answer
verified

In simple linear regression,the divisor of the standard error of estimate $S _ { e }$ is n - 1;simply because there is only one explanatory variable of interest.

Correct Answer
verified

Correct Answer
verified

Correct Answer
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