Suppose that a researcher collects data on test scores of schools in Massachusetts and obtains the regression results in table below. The dependent variable is Test Score, the average test score recorded in a given school; STR is the stu- dent teacher ratio in that school; and log(Income) is the log of the average income recorded in the county where the school is located. Estimate Std. Error t value Pr(> ) Bo: "Intercept) 619.39 93.48 6.63 0.00 B1 : STR -13.65 2.77 -4.93 0.00 B2: log(Income) 106.83 49.87 2.14 0.03 Ba: log(Income)? -24.42 6.57 -3.72 0.00 BA: STR x log( Income) 4.48 0.94 4.79 0.00 Table 1: Regression OutputYou did same work in (b) with log(Income) = 3.5. The expected change of an increase in STR of 3 students per teacher was 6.091, and a 95% confidence interval for the change in TestScore was (2.30038, 9.88149]. Is the expected change for an increase in STR of 3 units different for a school with log(Income) = 2.5, compared to a school with log(Income) = 3.5, at the 5% significant level? Explain and interpret the meaning eco- nomically