Using the following data (next page) identify the value of Y when X=0 (), the va

Question

Using the following data (next page) identify the value of Y when X=0 (), the value of each the Beta Coefficient and the t statistic for each variable. Compute the correlation coefficient (R2) and the Durbin Watson Statistic. Use the attached tables to determine the linearity of the regression and the independence of the errors. (21) points)
i. R2 = ______ (2 pts)
ii. = ______ (1pt)
iii. B1 = ______ (1pt)
iv. B2 = ______ (1pt)
v. B3 = ______ (1pt)
vi. t1 = ______ (1pt) Is there evidence of linearity here? Yes ____ No____ (2pts)
vii. t2 = ______ (1pt) Is there evidence of linearity here? Yes ____ No____ (2pts)
viii. t3 = ______ (1pt) Is there evidence of linearity here? Yes ____ No____ (2pts)
ix. Durbin Watson ________ (4 pts) Is there evidence of relation between the errors here (autocorrelation)? Yes ____ No____ (2pts)

SUMMARY OUTPUT
Regression Statistics
Multiple R 0.904955
R Square
Adjusted R Square 0.710311
Standard Error 2571188
Observations 9

ANOVA
df SS   MS
Regression 3 1.49513E+14   4.98E+13
Residual   5 3.3055E+13 6.61E+12
Total 8   1.82568E+14

Coefficients Standard Error   t Stat
Intercept 34626491 6641071.82   5.213991
7.298198   -3990148   1004255.617   -3.97324
0.004371   -8E+08 473551225.5   -1.69973
0.8125 -2897602 3931693.071   -0.73699

RESIDUAL OUTPUT
Observation   Predicted 18017072.9195074 Residuals
1   15184908   2234091.836
2 8766747 -1382648.39
3   1119566   3511375.58
4   4236248 -491090.8659
5 3697550   7360.575538
6 3656606   -392738.8168
7   1381127 1294982.439
8   5362241 -2790270.839
9   4556132 -1991061.518

Explanation / Answer

i) R2 =(0.904955)2 =0.819

ii. B1 =7.29

iv. B2 = 0.0043
v. B3 = 0.8125
vi. t1 = -3.97
vii. t2 = -1.699
viii. t3 = -0.737

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