1) Which is not a name often given to an independent variable that takes on just
ID: 3181035 • Letter: 1
Question
1) Which is not a name often given to an independent variable that takes on just two values (0 or 1) according to whether or not a given characteristic is absent or present?
Select one:
a. Absent variable
b. Binary variable
c. Dummy variable
2) A fitted multiple regression equation is Y = 12 + 3X1 - 5X2 + 7X3 + 2X4. When X1 increases 2 units and X2 increases 2 units as well, while X3 and X4 remain unchanged, what change would you expect in your estimate of Y?
Select one:
a. Decrease by 2
b. Decrease by 4
c. Increase by 2
d. No change in Y
3) A log transformation might be appropriate to alleviate which problem(s)?
Select one:
a. Heteroscedastic residuals
b. Multicollinearity
c. Autocorrelated residuals
4) A high leverage observation will have:
Select one:
a. an unusual value of the observed Y.
b. unusual values of one or more X's.
c. a large standardized residual.
5) Which of the following would be most useful in checking the normality assumption of the errors in a regression model?
Select one:
a. The t statistics for the coefficients
b. The F-statistic from the ANOVA table
c. The histogram of residuals
d. The VIF statistics for the predictors
6) Simple tests for nonlinearity in a regression model can be performed by
Select one:
a. squaring the standard error.
b. including squared predictors.
c. deleting predictors one at a time.
7) Heteroscedasticity of residuals in regression suggests that there is:
Select one:
a. nonconstant variation in the errors.
b. multicollinearity among the predictors.
c. non-normality in the errors.
d. lack of independence in successive errors.
Explanation / Answer
1. a) absent variable (which is not given to an independent variable with two outcomes)
2.b) decrease by 4 ( 3*2 - 5*2 = -4)
3.c) autocorrelated residuals
4.c) a large standardised residual
5.c) histogram of residuals ( as histogram gives the shape of the residual variable s)
6.c) deleting predictors one at a time
7.a) no constant variation in the error
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