Please help with the following statistics question. The first attachment is the background information, the second is the question:

A researcher is interested in using regression analysis to estimate Gross Domestic Product (GDP) on current economic factors. He tried to model y;, the GDP as a function of Ti,1, the amount of business investment. Also, the researcher is interested in including a dummy variable 1,2 to account for a difference between with and without the stimulus monetary policy. The researcher collected n = 30 observations and considered two different models. Model 1: E(yi) = Bo + BIti,1 + B2x1 + B3xi,2 + BATi,ITi,2 + Box Xi,2. Model 2: E( yi) = Bo + BIti,1 + B2 27,1. After fitting the model, two printouts are given as follow. Table 1: Model 1: GDP versus :41, $4,1-8q, 4,2, 14,1412, 14,1-8954,2 Predictor Coef SE Coef Constant 776.4 144.5 0.10418 0.01388 bs-Thr -0.00000223 0.00000033 Ti2 232 1094 -0.00914 0.09829 T4,1-8971,2 0.00000027 0.0000022 S=15.5829 R-Sq-97.2% Table 2: Model 2: GDP versus $4,1, $4,1-59 Predictor Coef SE Coef Constant 197.5 578.9 0.14921 0.05551 T4,1-59 -0.00000295 0.00000132 S=65.4523 R-Sq=48.3%(a) Fill in the missing numbers of the AnalysisofVariance table for the Model 1 and test at 5% level whether the model is of any use in predicting yi? Please write down (1) critical values and [2) make conclusion based on rejection region. Analysis of Variance Source DF SS MS F Regression Residual Error Total (b) Suppose the researcher has a hypothesis that GDP will increase at a decreasing rate as business investment increase. test the hypothesis at 5% significant level using Model 2 (c) Does the data provide sufficient evidence to indicate that the Model 1 contributes more information for the prediction of yicomparing with Model 2 at 5% significant level