1. A real estate builder wishes to determine how house size (House) is influenced by family income (Income), family size (Size), and education of the head of household (School). House size is measured in hundreds of squa
...
1. A real estate builder wishes to determine how house size (House) is influenced by family income (Income), family size (Size), and education of the head of household (School). House size is measured in hundreds of square feet, income is measured in thousands of dollars, and education is measured in years. The builder randomly selects 50 families and runs the multiple regression. The business literature involving human capital shows that education influences an individual’s annual income. Combined, these may influence family size. With this in mind, what should the real estate builder be particularly concerned with when analyzing the multiple regression model?
a) randomness of error terms
b) collinearity
c) normality of residuals
d) missing observations
ANSWER:
b
TYPE: MC DIFFICULTY: Moderate
KEYWORDS: collinearity, assumption
2. A microeconomist wants to determine how corporate sales are influenced by capital and wage spending by companies. She proceeds to randomly select 26 large corporations and record information in millions of dollars. A statistical analyst discovers that capital spending by corporations has a significant inverse relationship with wage spending. What should the microeconomist who developed this multiple regression model be particularly concerned with?
a) randomness of error terms
b) collinearity
c) normality of residuals
d) missing observations
ANSWER:
b
TYPE: MC DIFFICULTY: Moderate
KEYWORDS: collinearity, assumption
3. In multiple regression, the procedure permits variables to enter and leave the
model at different stages of its development.
a) forward selection
b) residual analysis
c) backward elimination
d) stepwise regression
ANSWER:
d
TYPE: MC DIFFICULTY: Easy
KEYWORDS: stepwise regression, model building
4. A regression diagnostic tool used to study the possible effects of collinearity is
a) the slope.
b) the Y intercept.
c) the VIF.
d) the standard error of the estimate.
ANSWER:
c
TYPE: MC DIFFICULTY: Easy
KEYWORDS: variance inflationary factor, collinearity
5. Which of the following is not used to find a "best" model?
a) adjusted r2
b) Mallow's Cp
c) odds ratio
d) all of the above
ANSWER:
c
TYPE: MC DIFFICULTY: Moderate
KEYWORDS: model building
6. The Variance Inflationary Factor (VIF) measures the
a) correlation of the X variables with the Y variable.
b) correlation of the X variables with each other.
c) contribution of each X variable with the Y variable after all other X variables are included in the model.
d) standard deviation of the slope.
ANSWER:
b
TYPE: MC DIFFICULTY: Easy
KEYWORDS: variance inflationary factor, collinearity
7. The Cp
statistic is used
a) to determine if there is a problem of collinearity.
b) if the variances of the error terms are all the same in a regression model.
c) to choose the best model.
d) to determine if there is an irregular component in a time series.
ANSWER:
c
TYPE: MC DIFFICULTY: Easy
KEYWORDS: C-p statistic, model building
CONTINUED.........
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