Refer to the table of estimated regressions below, computed using data for 1999 from all 420 K-6 and K-8 districts in California, to answer the following question. The variable of interest, test scores, is the average of the reading and math scores on the Stanford 9 Achievement Test, a standardized test administered to fifth-grade students. School characteristics (average across the district) include enrollment, number of teachers (measured as "full-time equivalents"), number of computers per classroom, and expenditure per student. Results of Regressions of test scores on the Student-Teacher Ratio and Student Characteristic Control Variables Using California Elementary School Districts. Dependent variable: average test score in the district. Regressor Student-teacher ratio (✗₁) Percent English learners (X2) Percent elegible for subsidized lunch (X3) Percent on public income assistance (X4) (1) - 2.79** (0.59) (2) - 1.36* (0.45) - 0.638** (0.034) (3) - 1.26** (0.28) - 0.113** (0.039) - 0.507** (0.027) (4) - 1.55** (0.36) - 0.484** (0.038) - 0.749** (0.069) (5) - 1.33** (0.23) - 0.116** (0.035) - 0.535** (0.032) Compute the R² for each of the regressions. 0.043 (0.059) 694.6** 681.7** 699.4** 701.6** 704.8** Intercept (10.8) (8.3) (5.6) (6.7) (5.2) Summary Statistics and Joint Tests SER 18.72 14.47 9.49 11.55 9.14 Ŕ² 0.044 0.492 0.751 0.644 0.763 n 450 450 450 450 450 These regressions were estimated using data on K-8 school districts in California. Heteroskedastic-robust standard errors are given in parentheses under coefficients. The individual coefficient is statistically significant at the *5% level or **1% significance level using a two-sided test. 1. The R² for the regression in column (1) is: 0.046 2. The R² for the regression in column (2) is: 0.494 3. The R² for the regression in column (3) is: 0.753 4. The R² for the regression in column (4) is: 0.646 5 The R²² for the regression in column (5) is: 0 765 Next 4. The R* for the regression in column (4) is: 0.646| 5. The R² for the regression in column (5) is: 0.765 (Round your response to three decimal places) Construct the homoskedasticity-only F-statistic for testing ẞ3 = ẞ4 = 0 in the regression shown in column (5). The homoskedasticity-only F-statistic for the test is: 255.66 (Round your response to two decimal places) Is the homoskedasticity-only F-statistic significant at the 5% level? A. Yes. B. No. Test B3 B40 in the regression shown in column (5) using the Bonferroni test. Note that the 1% Bonferroni critical value is 2.807. The t-statistic for ẞ3 in the regression in column (5) is: Is the Bonferroni test significant at the 1% level? A. Yes. B. No. (Round your response to three decimal places) The t-statistic for ẞ4 in the regression in column (5) is: (Round your response to three decimal places) Construct a 99% confidence interval for B₁ for the regression in column (5). The 99% confidence interval is: - 1.923 -0.737] (Round your response to three decimal places)