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All the regression assumptions lie on the residuals, for both simple and multiple regression.
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- (2)What would the consequence be for a regression model if theerrors were not homoscedastic?In multiple regression model: what is it means for a variable to be significant? Explain the meaning of the significant variable.What are the measures of fit that are commonly used for multiple regressions? How can an adjusted R2 take on negative values?
- In a regression problem with 1 output variable and with a total number of 100 possible input variables, what is the number of all possible models with three input variables?Which of the following statements concerning the least squares regression of Y on X depicted in the graph below is true?Introductory Econometris: A Modern Approach 4th edition, Chapter 17 Problem 1CE: What is the command in R in order to run the "White heteroskedasticity-consistent standard errors & covariance"? In other words, I would like to run the new regression with robust standard errors in it.
- What is a linear regression model? What is measured by the coefficients ofa linear regression model? What is the ordinary least squares estimator?What is difference between regression model, and estimated regression equation?2. Consider a two variable regression model, which satisfies all the Gauss Markov assumptions except that the error variance is proportional to X² i.e.E(u?) = o²X? Y₁ = B₁ + B₂X₁ + Ui How would you obtain the best linear unbiased estimates from the above regression.