Would like assistance on my stats assignment, all excel work should be copied onto a word document...

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Would like assistance on my stats assignment, all excel work should be copied onto a word document please.Thank you so muchNOTE1: Please note that in parts h) and i) you can assume E(y0|x0)=exp{E(log(y0|x0))}. That is, you can use the exponentated log prediction as the actual point prediction you are asked to find. [More detail: In forecasting there is an issue with the taking the expectation of a log (non-linear) transformation to recover the underlying prediction of interest. In particular, E[log(Y|X)] does not equal log E(Y|X). Depending upon assumptions a correction factor may be used, but without this there is no consensus on the 'best' way to handle this problem].
	
Document Preview: ECMT1020 Written Assignment 
Due 2pm Friday June 7, 2013 
 
Instructions 
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Robert · Accepted Answer

a) Scatter Plot between Revenue and Budget is as given below: 
 
 
Scatter Plot of Revenue v/s Screens is as given below: 
 
 
 
The Correlation Matrix for the three variables is as given below: 
 

Correlations 
  REVENUE BUDGET SCREENS 
REVENUE Pearson Correlation 1 .518 .745
BUDGET Pearson Correlation .518 1 .685
SCREENS Pearson Correlation .745 .685 1
b) Regression with Revenue as dependent variable and Budget and Screens as 
independent variables is as follows:
Model Summary 
Model R R Square 
Adjusted R 
Square 
Std. Error of the 
Estimate 
1 .745
a
 .555 .554 4879108.119
ANOVA
b
 
Model Sum of Squares df Mean Square F Sig. 
1 Regression 2.932E16 2 1.466E16 615.821 .000
a
 
Residual 2.354E16 989 2.381E13   
Total 5.286E16 991
Coefficients
a
 
Model 
Unstandardized Coefficients 
Standardized 
Coefficients 
t Sig. B Std. Error Beta 
1 (Constant) -3.644E6 356720.901  -10.216 .000 
BUDGET .003 .005 .015 .529 .597 
SCREENS 56394.411 2237.948 .734 25.199 .000 
a. Dependent Variable: REVENUE
The regression line is as follows: 
Revenue = -3.64 * 10
6
 + .003* Budget + 56394.411*Screens 
It can be seen that regression coefficient for Budget is not significant as p value for t statistic 
is more than 0.05. Regression coefficient for Screens is significant at 5% level of 
significance. This shows that a one unit change in Screens leads to a 56394.411 units change 
in Revenue.
c) Scatter Plot of Residuals v/s Budget is as given below:
 

Scatter Plot of Residual v/s Screens is as given:
 
Histogram of standardized Residuals is given below:
From the histogram we can observe that Residuals do not follows Normal Distribution thus 
the assumption of normality is violated. From the Scatter plot of Residuals v/s Screens and 
Budget, it can be seen that there are many outliers. Thus the non normality of residuals could 
be due to outliers.
d) Now, we transform the variables and take the natural logarithms and obtain the 
regression line as follows:
ANOVA
b
 
Model Sum of Squares df Mean Square F Sig. 
1 Regression 238.858 2 119.429 305.479 .000
a
 
Residual 386.656 989 .391   
Total 625.515 991    
a. Predictors: (Constant), LnScr,

Would like assistance on my stats assignment, all excel work should be copied onto a word document please. Thank you so much NOTE1: Please note that in parts h) and i) you can assume...

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