CHAPTER 11: REGRESSION ANALYSIS: STATISTICAL INFERENCE Q & A EXAM WELL RATED A+ DOWNLOAD TO SCORE A

CHAPTER 11: REGRESSION ANALYSIS: STATISTICAL
INFERENCE Q & A EXAM WELL RATED A+ DOWNLOAD TO
SCORE A

CHAPTER 11: Regression Analysis: Statistical Inference




MULTIPLE CHOICE


1. Which of the following is not one of the assumptions of regression?
a. There is a population regression line
b. The response variable is normally distributed
c. The standard deviation of the response variable increases as the explanatory
variables increase
d. The errors are probabilistically independent

ANS: C PTS: 1 MSC: AACSB: Analytic | AACSB: Regression
Analysis


2. The error term represents the vertical distance from any point to the
a. estimated regression line
b. population regression line
c. value of the Y’s
d. mean value of the X’s

ANS: B PTS: 1 MSC: AACSB: Analytic | AACSB: Regression
Analysis


3. Which of the following is true regarding regression error, e
a. it is the same as a residual
b. it can be calculated from the observed data
c. it cannot be calculated from the observed data
d. it is unbiased

ANS: C PTS: 1 MSC: AACSB: Analytic | AACSB: Regression
Analysis

, CHAPTER 11: REGRESSION ANALYSIS: STATISTICAL
INFERENCE Q & A EXAM WELL RATED A+ DOWNLOAD TO
SCORE A

4. The term autocorrelation refers to:
a. analyzed data refers to itself
b. sample is related too closely to the population
c. data are in a loop (values repeat themselves)
d. time series variables are usually related to their own past values

ANS: D PTS: 1 MSC: AACSB: Analytic | AACSB: Regression
Analysis


5. In regression analysis, multicollinearity
refers to:
a. the response variables being highly correlated
b. the explanatory variables being highly correlated
c. the response variable(s) and the explanatory variable(s) are highly correlated
with one another
d. the response variables are highly correlated over time.

ANS: B PTS: 1 MSC: AACSB: Analytic | AACSB: Regression
Analysis


6. Another term for constant error variance is:
a. homoscedasticity
b. heteroscedasticity
c. autocorrelation
d. multicollinearity

ANS: A PTS: 1 MSC: AACSB: Analytic | AACSB: Regression
Analysis

, CHAPTER 11: REGRESSION ANALYSIS: STATISTICAL
INFERENCE Q & A EXAM WELL RATED A+ DOWNLOAD TO
SCORE A

7. Time series data often exhibits which of the following characteristics?
a. homoscedasticity
b. heteroscedasticity
c. autocorrelation
d. multicollinearity

ANS: C PTS: 1 MSC: AACSB: Analytic | AACSB: Regression
Analysis


8. A scatterplot that exhibits a “fan” shape (the variation of Y increases as X increases) is an
example of:
a. homoscedasticity
b. heteroscedasticity
c. autocorrelation
d. multicollinearity

ANS: A PTS: 1 MSC: AACSB: Analytic | AACSB: Regression
Analysis


9. Which of the following definitions best describes parsimony?
a. Explaining the most with the least
b. Explaining the least with the most
c. Being able to explain all of the change in the response variable
d. Being able to predict the value of the response variable far into the future

ANS: A PTS: 1 MSC: AACSB: Analytic | AACSB: Regression
Analysis


10. Which of the following is the relevant sampling distribution for regression coefficients?
a. Normal distribution
b. t-distribution with n-1 degrees of freedom
c. t-distribution with n-1-k degrees of freedom
d. F-distribution with n-1-k degrees of freedom

, CHAPTER 11: REGRESSION ANALYSIS: STATISTICAL
INFERENCE Q & A EXAM WELL RATED A+ DOWNLOAD TO
SCORE A

ANS: C PTS: 1 MSC: AACSB: Analytic | AACSB: Regression
Analysis


11. The t-value for testing is calculated using which of the following equations:
a. n – k -
1 b.

c.

d.


ANS: D PTS: 1 MSC: AACSB: Analytic | AACSB: Regression
Analysis


12. In the standardized value , the symbol represents the:
a. mean of
b. variance of
c. standard error of
d. degrees of freedom of

ANS: C PTS: 1 MSC: AACSB: Analytic | AACSB: Regression
Analysis


13. The value k in the number of degrees of freedom, n-k-1, for the sampling distribution of the
regression coefficients represents:
a. the sample size
b. the population size