3. Let Google% and S&P% denote daily returns. Mult R 0.6209 For 4/2/13 to 5/9/13, Google% was regressed on R Square 0.3856 Adj R Sq 0.3619 S&P%. Test at alpha-level 5%, as usual. Stand Err 1.1627 Obs 28 (a) Find > when S&P% = 3. ANOVA SS MS F Sign F Reg 1 22.058 16.316 0.0004 Resid 26 35.149 1352 22.058 (b) Explain what population characteristic is being Total 27 57.207 estimated in (a). Coel 5.E. t Stat P-volve Low 95%% Up 75% Intercept 0. 1394 0.2280 0.6255 U.5369 -0.3139 U.5980 (c) Give an approximate 95% prediction interval S&PA 1.0653 D.2637 4.0393 0.0004 0.5232 16074 for Google% when S&P%=3. (d) In words, without using Greek symbols, state the null and alternate hypotheses for the test being performed in the S&P% row of the Excel output. (e) Conceptually, when would the null hypothesis in the above test be rejected? (f) Sketch the relevant t-distribution for the S&P% row. Show and label the following items: t-critical values; t-statistic and its negative; rejection region; alpha; and p-value. (g) Define the p-value as applied to this setting, using the numeric values 0.0004 and 4.0393. (h) What parameter is being estimated by 0.2637 in the S&P% row? (i) Explain the nature of the daughter population involved in the preceding