The estimated regression relating the average test score of students and district income is as follows: TestScore = 600.1 + 5.02 Income - 0.096 Income + 0.00069 Income, (5.1) (0.71) R = 0.555. (0.029) (0.00035) a. Predict the average test score of a district with the income 10$ (note that unit of income is 1000$). b. Write the 99$ confidence interval of 3 terms of incomes. c. Which income parameter is statistically significant at 99% confidence level? 2. Logarithmic transformation With the same data, the researcher decides to estimate the test scores with the logarithm of the income, as follows: = 0.561. TestScore =557.8 + 36.42ln(Income), R2 = (3.8) (1.40) a. Predict the average test score of a district with the income 10$ (note that unit of income is 1000$). b. When we interpret the coefficient of the log variable, we use the following rule: A 1% change in X (the logged predictor) predicts a change of 0.01*beta in Y (outcome variable). Using this rule, write the interpretation of the coefficient of the In(Income).