Using the estimation results in Question 5, test the null hypothesis that the mean test score...

  

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Using the estimation results in Question 5, test the null hypothesis that the mean test score in districts with low student-teacher ratio (STR <17) is equal to the mean test score in districts with high student-teacher ratio (STR ≥ 17). For this question, the standard error type in R has to be either "stata" or "HC1". Choose the correct statement: a. We do not reject the null hypothesis at the 10% significance level. b. We do not reject the null hypothesis at the 5% significance level. C. We do not reject the null hypothesis at the 1% significance level. d. We do not reject the null hypothesis regardless of the significance level. Note that this exercise replicates Section 5.3 in Stock and Watson, but with the MA data instead of CA data. Hence, it would be helpful to read the section once again. Generate a new variable D in R that equals either 0 or 1, depending on whether the student-teacher ratio is less than 17, i.e., i D = i 1 if the student teacher ratio in i district < 17 O if the student - teacher ratio in ith district ≥ 17 Estimate the population regression model TestScore =a+a_D.+e 1 i i 0 i where E[e ID.]=0. Note that different notations (a a e.) are used instead of (B, B₁, u.) because the regression model in this question is different from i 0' 1' the one in Question 2. What is the OLS estimate for the conditional expectation, 0' 1' Report your answer to two decimal places. E[TestScore STR <17] Using the estimation results in Question 5, test the null hypothesis that the mean test score in districts with low student-teacher ratio (STR <17) is equal to the mean test score in districts with high student-teacher ratio (STR ≥ 17). For this question, the standard error type in R has to be either "stata" or "HC1". Choose the correct statement: a. We do not reject the null hypothesis at the 10% significance level. b. We do not reject the null hypothesis at the 5% significance level. C. We do not reject the null hypothesis at the 1% significance level. d. We do not reject the null hypothesis regardless of the significance level. Note that this exercise replicates Section 5.3 in Stock and Watson, but with the MA data instead of CA data. Hence, it would be helpful to read the section once again. Generate a new variable D in R that equals either 0 or 1, depending on whether the student-teacher ratio is less than 17, i.e., i D = i 1 if the student teacher ratio in i district < 17 O if the student - teacher ratio in ith district ≥ 17 Estimate the population regression model TestScore =a+a_D.+e 1 i i 0 i where E[e ID.]=0. Note that different notations (a a e.) are used instead of (B, B₁, u.) because the regression model in this question is different from i 0' 1' the one in Question 2. What is the OLS estimate for the conditional expectation, 0' 1' Report your answer to two decimal places. E[TestScore STR <17]

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b we will reject null ... View the full answer