The simple linear regression assumption 1 to 4 is needed to prove the unbiasedness of ordinary least squares b. variance of ordinary least squares c. expected value of μ and x is zero all of the statements are correct d. O a. a O b. b О с. с ○ d. d
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- Please answer fast please helpIf the error term is correlated with any of the independent variables, the OLS estimators are: a. biased and consistent. b. unbiased and inconsistent. C. biased and inconsistent. d. unbiased and consistent. O a. a O b. b О с. с O d. dIf the estimator is consistent and the asymptotic variance is smaller than all other consistent estimators of then Ô is asymptotic efficient. O True False
- Please no written by hand The assumption of normally distributed errors means that... A. errors can be ignored when doing regression modelling. B. the OLS estimators can also be assumed to be normally distributed since they are a linear functions of the errors. C. the OLS estimators can also be assumed to be normally distributed since they are BLUE. D. the OLS estimators can also be assumed to be normally distributed since they are minimum variance. E. the regression model will not be subject to specification error.1- the locus of conditional means of Y fort he fixed values of X is the. Please select one; a) intercept line b) linear regression line c) population regression line d) conditional expectation function m2- Homoskedasticity means that the variance of the dependent term is constant. True False
- 8. Which of the following best describes the linear probability model? The model is the application of the linear multiple regression model to a binary dependent variable The model is an example of probit estimation The model is another form of logit estimation The model is the application of the multiple regression model with a binary variable as at least one of the regressors OOConsider the OLS estimator 3;. Under the Gauss-Markov assumptions, O the estimator is the best linear unbiased estimator. O the estimator is asymptotically normally distributed. O the estimator has the properties stated in the other three possible answers. O the estimator is consistent.Y 70 12 50 9 57 60 14 43 9 52 11 i. Find the estimators for Bi and B2 correct to decimal points and fit the regression equation for X and Y when X is the explanatory variable. Interpret the results from the obtained equation. calculate the sum of error squared. Find the variance of the sum square error ii. iii. iv. Find the standard error for B2 Find the coefficient of correlation and give its interpretation V. vi.
- IV. 得分 What information can be obtained from this summary output? a to enter = 0.05, a to remove = 0.05 Analysis of Variance Source DF Adi sS Adi MS F-Value P-Value www Regression 4 37260200 9315050 45. 23 0. 000 0. 000 0. 000 Poten 1 4727687 4727687 22. 95 AdvExp 4630364 4630364 22. 48 Share 1 3009401 3009401 14. 61 0.001 Accounts 1 2129972 2129972 10. 34 0.004 Error 20 4119349 205967 Total 24 41379549 R-sq R-sq (adi) R-sq (pred) 453. 836 90. 04% 88. 05% 85. 97% Coefficients Term Coef SE Coef T-Value P-Value VIF Constant -1442 424 -3. 40 0,003 Poten 0. 03822 0. 00798 4. 79 0. 000 1. 83 AdvExp 0. 1750 0. 0369 4. 74 0. 000 1. 15 Share 190. 1 49. 7 3. 82 0.001 1.74 Accounts 9. 21 2. 87 3. 22 0. 004 1. 99 Fits and Diagnostics for Unusual Observations Std Obs Sales Fit Resid Resid www 10 4876 3942 934 2. 14 R5- zero correlation does not necessarily imply independence between the two variables. This statement is Please select one; a) true www b) depends on mean value of X and Y c) depends on r wwww w d) falsethe option for all the questions is on the the first square