Consider a simple linear model Yi = B1 + B2Xi + us. Suppose that we have a sample with 30 observations and run OLS regression to get the estimates for B, and B2. We get B2 = 3.5, N E(X, - X)2 = 175, TSS = 560 (total sum of squares), and RSS = 340 (residual sum of i=1 squares). 1. [2 points] Calculate the standard error of B2. 2. [4 points] Test the null hypothesis Ho : B2 = 3 against the alternative hypothesis H1 : B2 + 3 (use 5% significance level). 3. [4 points] How do we measure the goodness of fit of a regression? What can you say about the goodness of fit of this regression given the information above