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Exam 15: Multiple Regression

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Question 31

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SCENARIO 15-6 -True or False: Referring to Scenario 15-6, the variable should be dropped to remove collinearity?

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Question 32

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Question 33

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True or False: One of the consequences of collinearity in multiple regression is biased estimates on the slope coefficients.

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 In years.The builder randomly selected 50 families and constructed the multiple regression Model.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?

SCENARIO 15-6 -True or False: Referring to Scenario 15-6, the variable should be dropped to remove collinearity?

True or False: The Variance Inflationary Factor (VIF)measures the correlation of the X variables with the Y variable.

The logarithm transformation can be used

SCENARIO 15-6 -True or False: Referring to Scenario 15-6, there is reason to suspect collinearity between some pairs of predictors based on the values of the variance inflationary factor.

True or False: One of the consequences of collinearity in multiple regression is inflated standard errors in some or all of the estimated slope coefficients.

SCENARIO 15-1 -Referring to Scenario 15-1, what is the correct interpretation of the coefficient of multiple Determination?

True or False: Two simple regression models were used to predict a single dependent variable. Both models were highly significant, but when the two independent variables were placed in the same multiple regression model for the dependent variable, R2 did not increase substantially and the parameter estimates for the model were not significantly different from 0.This is probably an example of collinearity.

SCENARIO 15-1 -True or False: Referring to Scenario 15-1, a more parsimonious simple linear model is likely to be statistically superior to the fitted curvilinear for predicting sale price (Y).

SCENARIO 15-1 -Referring to Scenario 15-1, what is the p-value associated with the test statistic for testing Whether there is an upward curvature in the response curve relating the demand (Y) and the price (X) ?

The Cp statistic is used