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Question 1 Heteroskedasticity is a violation of which assumption of the multiple regression model? a) E(ei)...

Question 1

Heteroskedasticity is a violation of which assumption of the multiple regression model?

a) E(ei) = 0

b) cov(ei, ej) = 0 where i≠j

c) The values of each independent variable xik are not random

d) var(ei) = σ2

Question 2

You have estimated a multiple regression model with 6 explanatory variables and an intercept from a sample with 46 observations. What is the critical value (or t-crit) if you want to perform a one-tailed t test at the 1% level of significance?

a) 2.704

b) 2.423

c) 2.426

d) 2.708

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Answer #1

D is right option.

Heteroskedasticity is defined as a violation of assumption of constant variances for different observations of the error term. the error term's variance can change depending on the observation...often occurs when there is a wide disparity between the largest ad the smallest observed value of the dependent variable We would expect the error term variances to e larger for larger observations, nut the error term distribution for small observations might have a small variance.

Sorry for second one i tried hard but couldn't find its answer.. Really sorry for that

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