Multiple Regression for DJIA

Consider the following regression model:

? D = percent change in DJIA (Dow Jones Ind. Avg.);
? O = per barrel price of oil;
? I = interest rates (in real number percentages: 6%, etc);
? E = corporate earnings growth rate;
? G = GDP growth rate.
? R2 = 0.8500
? F = 24
? F(Se) = 1.0
? D = 2.0 - 3.0I + 1.5E - 1.2O + 2.0G
(Sbi) (1.9) (1.1) (0.3) (0.9) (0.7)

(1).What is the predicted impact on the DJIA if the interest rate dropped 1% next year?
(2). How would the DJIA be affected if the GDP fell by 1% next year?
(3). Are any of the explanatory variables insignificant?
(4). Construct the 95% interval estimate of the effect of interest rate changes on the DJIA.
(5). Predict the impact on the DJIA when I = 6.0%, E = 20.0%, O = $20, and G = 8.0%.
Then construct 90 % prediction interval.
(6). How well does the model explain variation in the DJIA?
(7). Suppose you believe that the market performs better when there is a Republican
administration in the White House. Given yearly data, how would you capture the
effect of political party on the DJIA?
(8). Traditionally, for every 1% increase in GDP growth the DJIA would rise by 3%. You
believe that GDP growth rate has much smaller influence on the stock market. Your
data consists of 200 observation months. Formally test your conjecture that GDP
growth has less than the traditional impact on the DJIA. Allow a 2.5% probability of
making a type one error.
(9). If, in fact, every percent increase in GDP growth rate only boosts the DJIA by 2%,
determine the probability of erroneously accepting the traditional belief.