Suppose that the error term u in regression y = Bo + B1x + u is in-dependent of the explanatory variable x, and it takes on the values-2, –1,0, 1, and 2 with equal probability of 1/5.Select TRUE or FALSE:(a) The Gauss-Markov assumptions are violated.(b) Normal distribution assumption of the error term is violated.

We have to answer questions based on Gauss Markov theorem.

Answered: Suppose that the error term u in…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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Consider the fitted values from a simple linear regression model with intercept: yˆ = 5 + 6x. Assume that the total number of observations is n = 302. In addition, the R-squared of the regression is R2 = 0.6 and Pn i=1(xi − x¯) 2 = 15, where ¯x is the sample mean of x. Under the classical Gauss-Markov assumptions standard error of the estimated slope coefficient = 0.0365 value of the t-statistic for the null hypothesis H0 : the slope coefficient is equal to 0 versus H1 : the slope coefficient is different from 0 = 164.3836 What is the value of the F-statistic for the null hypothesis H0 : the slope coefficient is equal to 0 versus H1 : the slope coefficient is different from 0? Do the p-values of the t- and F-tests differ from each other? Justify your answer.
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Consider the following regression:Y = β0 + B1X1 + β2X2 + β3X1 · X2+ Ewhere• Y = wage• X1 = years of education • X2 =0 if race = white 1 if race =black-Write out the interpretations of β1 ,β2 , and β3in terms of expectations. Takethe expectation of Y conditional on race=white. take the expectation conditional onwage=black. Compute these expectations when education=0. -- Suppose β0 > 0, β1> 0, β2 < 0, β3 > 0. Sketch the race-specific returns to education?
In reading the results of a multiple regression analysis that contained 4 predictor variables, the researcher noticed a column labeled Beta. Two of the Beta’s were positive and two were negative. He concluded that a.) Beta’s that were positive were statistically significant b.) Beta’s that were positive had more of an effect c.) Beta’s that were positive were associated with increases in the criterion variable d.) Beta’s that were positive did not affect the criterion because they were “controlled for…”

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