A model: Test Score = 698.9 – STR
with(9.47) (0.48)
are homoskedasticity-only standard errors.
calculate the miss coefficient of str
A model: Test Score = 698.9 – STR with(9.47) (0.48) are homoskedasticity-only standard errors. calculate the miss coefficient of str
Shortly before you are making a group presentation on the testscore/student-teacher ratio results, you realize that one of your peers forgot to type all the relevant information on one of your slides. Here is what you see: TestScore = 698.9 - STR, R = 0.051, SER =18.6 SE: for intercept(9.47) and coefficient(0.48). In addition, your group member explains that he ran the regression in a standard spreadsheet program, and that, as a result, the standard errors in parenthesis are homoskedasticity-only...
You have estimated the relationship between test scores and the student-teacher ratio under the assumption of homoskedasticity of the ermor tems. The regression output is as follows: Test Score-698.9-228x STR, and the standard error on the slope is 0.48. The homoskedasticity-only 'overalir regrssion F-staisatic for the hypothesis that the regression R is zero is approximately OA. 1.96. O B. 0.96 O C. 4.75 O D. 22.56.
You have estimated the relationship between test scores and the student-teacher ratio under the assumption of homoskedasticity of the error terms. The regression output is as follows: Test Score = 698.9 -2.28 x STR, and the standard error on the slope is 0.48. The homoskedasticity-only "overall" regression F-statistic for the hypothesis that the regression R is zero is approximately: O A. 4.75. O B. 22.56. O C. 0.96. OD. 1.96.
Explain the consequence of using homoskedasticity-only standard errors when in fact the errors are heteroskedastic for each of the following: a) The OLS estimators of β0and β1 b) Hypothesis tests for β1 c) A 95% confidence interval for β1 Thanks
How can I find the P-value? Please write down all of the
step
. reg testscr str, robust 420 Regression with robust standard errors Number of obs FC 1, 418 Prob F R-squar ed Root MSE 19.2 -0. 0000 -.0512 -18. 581 Robust Coef. Std. Err. [95% conf. interval] testscr str -cons 194892 698. 933 10.36436 -2.279808 -4.39 0.000 67.440.000 -3. 300 45 1.258671 678. 5602 719. 3057 Test Score = 698.9 _ 2.28 . STR (10.4) (0.52) SE(βο-10.4 and...
4. Consider the regression model, y1B22+ BKiK+ei -.. where errors may be heteroskedastic. Choose the most incorrect statement (a) The OLS estimators are consistent and unbiased (b) We should report the OLS estimates with the robust standard errors (c) The Gauss-Markov theorem may not apply (d) The GLS cannot be used because we do not know the error variances in practice (e) We should take care of heteroskedasticity only if homoskedasticity is rejected Consider the regression model, +BKIK+et e pet-1+...
Question 12 3 pts Consider the estimated multiple regression model using OLS, with the standard errors in parentheses below each estimated coefficient. There are 1,576 observations in the sample: Ỹ = 10 + 2x - 5X36 (3) (1.5) (2) Suppose the null hypothesis is that the true coefficient (population parameter) for X3 is equal to 1. The test statistic associated with this null hypothesis is: -3 0-2 O 2
Only need d
4.12. Typographical errors. Shown below are the number of galleys for a manuscript (X) and the total dollar cost of correcting typographical errors (Y) in a random sample of recent orders handled by a firm specializing in technical manuscripts. Since Y involves variable costs only, an analyst wished to determine whether regression-through-the-origin model (4.10) is appropriate for studying the relation between the two variablės. i: 1 23 ' 56 7 8910 11 12 x,: 7 12 10...
Only need d
4.12. Typographical errors. Shown below are the number of galleys for a manuscript (X) and the total dollar cost of correcting typographical errors (Y) in a random sample of recent orders handled by a firm specializing in technical manuscripts. Since Y involves variable costs only, an analyst wished to determine whether regression-through-the-origin model (4.10) is appropriate for studying the relation between the two variablės. i: 1 23 ' 56 7 8910 11 12 x,: 7 12 10...
Question 4 3 pts Consider the estimated multiple regression model using OLS, with the standard errors in parentheses below each estimated coefficient. There are 1,576 observations in the sample: Y = 10 + 2X2i - 5Xzi (3) (1.5) (2) Suppose that the sample mean of Y is 30. For the 18th observation (i=18) in the sample, the value of X2 is 50, the value of X3 is 16, and the value of Y is 20. The residual associated with the...