Need help with question 1, 2 and 3 :)

QUESTION 1 An economist has measured people's annual salary (in thousands of dollars) and their years of relevant job experience, thinking that a linear relationship between them might exist. Let the proposed regression relationship between Salary and experience be as follows: E(Salary) = Bo + B1 X Years of Experience and assume the output from running the regression is as follows: Call: Im(formula = Salary ~ Year, data = Income) Residuals: Min 1Q Median 3Q Max -53.650-20.256 0.127 18.423 65.596 Coefficients: Estimate Std. Error tvalue Pr(>)t]) Intercept) 31.8387 8.5565 3.721 0.00033** * Years 2.8205 0.3302 8.543 1.74e-13 ** * Signif. codes: 0 (* **) 0.001 **) 0.01 "* 0.05 "' 0.1"' 1 Residual standard error: 25.98 on 98 degrees of freedom Multiple R-squared: 0.4268, Adjusted R-squared: 0.421 F-statistic: 72.98 on 1 and 98 DF, p-value: 1.737e-13 Residual standard error: 8.044 on 445 degrees of freedom Multiple R-squared: 0.6914, Adjusted R-squared: 0.6886 F-statistic: 249.2 on 4 and 445 DF, p-value: O O C. Ho: Bo = 0 " H1: Bo * 0 O d. Ho: Bo = 0 H1: Bo > OQUESTION 2 Using the output in Q1, what is the correct pvalue for the test in Q1? 0 3- 0.000000000000174 o In. 1340-13 0 72- 0.00000393 0 d. 0.00033 QUESTION 3 What is the fitted regression model from this output in Q1? O a. E( Years of Experience ) = 2.8205 + 31.8387 x Salary O b. E(Salary) = 2.8205 + 31.8387 x Years of Experience O c. E(Salary) = 31.8387 + 2.8205 x Years of Experience d. E( Years of Experience ) = 31.8387 + 2.8205 x Salary