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Question: Histogram of residuals: 5. Comment on the Normality assumption for the residuals for this model….



Question: Histogram of residuals:5. Comment on the Normality assumption for theresiduals for thismodel....

Histogram of residuals:

Question: Histogram of residuals:5. Comment on the Normality assumption for theresiduals for thismodel....

5. Comment on the Normality assumption for the
residuals for this

model. In other word, has the normality assumption been
satisfied?

Explain your answer (Hint: you need to run Excel’s Histogram
feature

for Column of the Residuals).

6. Do you see any indication of
Multicollinearity? Explain why.

(Hint: Run the Correlation Matrix of the Independent Variables).
Can

you find any evidence of Multicollinearity without referring to
the

Correlation Matrix? Explain.

7. Do you see any Indication of
Autocorrelation? Calculate the value of the

Durbin-Watson test statistics, using the formula from your
Formula Sheet or

look below:

Question: Histogram of residuals:5. Comment on the Normality assumption for theresiduals for thismodel....

8. Do you see any indication of
Heteroscedasticity for the Variable X 3 ?

Copy and paste the residuals for this variable only. Demonstrate
and

Explain why.

Show transcribed image text 1 SUMMARY OUTPUT Regression Statistics 4 Multiple R 5 R Square 6 Adjusted R Square 7 Standard Error 8 Observations 0.78330504 0.613566786 0.612444739 61283.64107 1728 10 ANOVA MS Significance F 12 Regression 13 Residual 14 Total 51.02686E+13 2.05371E+12546.827741 0 1722 6.46729E+123755684663 17271.67359E+13 P-value Lower 95% Ue, 95% Lower 95.0% Coefficients Standard Error 41079.844416092.7207776.742446587 2.11868E-11 29129.9318353029.75699 29129.93183 53029.75699 6746.9460152139.7905883.153087061 0.001643392 2550.083661 10943.80837 2550.083661 10943.80837 261.8781794 0.9592086180.04692449 20.44154878 2.51646E-83 0.867173679 1.0512435560.867173679 1.051243556 92.405293433.578298102 25.82381087 1.4494E-12485.38702507 99.4235618 85.38702507 99.4235618 6496.7342442454.477224-2.646891233 0.008197595 -11310.80489-1682.663597-11310.80489 -1682.663597 t Stat Uper 95.0% 17 Intercept 18 x1 19 x2 20 x3 21 X4 22 x5 52.4017967-4.9975038246.39789E-07-364.6560536159.1003052-364.6560536159.1003052

1 SUMMARY OUTPUT Regression Statistics 4 Multiple R 5 R Square 6 Adjusted R Square 7 Standard Error 8 Observations 0.78330504 0.613566786 0.612444739 61283.64107 1728 10 ANOVA MS Significance F 12 Regression 13 Residual 14 Total 51.02686E+13 2.05371E+12546.827741 0 1722 6.46729E+123755684663 17271.67359E+13 P-value Lower 95% Ue, 95% Lower 95.0% Coefficients Standard Error 41079.844416092.7207776.742446587 2.11868E-11 29129.9318353029.75699 29129.93183 53029.75699 6746.9460152139.7905883.153087061 0.001643392 2550.083661 10943.80837 2550.083661 10943.80837 261.8781794 0.9592086180.04692449 20.44154878 2.51646E-83 0.867173679 1.0512435560.867173679 1.051243556 92.405293433.578298102 25.82381087 1.4494E-12485.38702507 99.4235618 85.38702507 99.4235618 6496.7342442454.477224-2.646891233 0.008197595 -11310.80489-1682.663597-11310.80489 -1682.663597 t Stat Uper 95.0% 17 Intercept 18 x1 19 x2 20 x3 21 X4 22 x5 52.4017967-4.9975038246.39789E-07-364.6560536159.1003052-364.6560536159.1003052

  

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