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].

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ECMT1020 Written Assignment Due 2pm Friday June 7, 2013 Instructions ? In order to complete this assignment, you will need the data set ‘Film data.xls’. ? This assignment must be done alone and is worth 10% of your final mark. ? You will be marked on the correctness of your answers as well as presentation. ? The assignment must be submitted both electronically and by hard-copy. The hard-copy version is to be submitted into the assignment boxes on level 2 of the Merewether Building. The electronic version must be submitted via the University Learning Management System (see 3 minute online tutorial for further details). ? Please submit only one single MS Word (or PDF) file. Do not submit multiple files. In particular, DO NOT submit MS Excel files. ? Late assignments will be penalised 20% of full marks per day and must be sent directly to the lecturer. ? You should familiarise yourself with the University’s policies regarding academic honesty and plagiarism and understand the following declaration: By submitting an assignment through the University Learning Management System, 1. I certify that: I have read and understood the University of Sydney Academic Dishonesty and Plagiarism Policy; 2. I understand that failure to comply with the above can lead to the University commencing proceedings against me for potential student misconduct under Chapter 8 of the University of Sydney By-Law 1999 (as amended); 3. This Work is substantially my own, and to the extent that any part of this Work is not my own, I have indicated that it is not my own by acknowledging the source of that part or those parts of the Work. 4. I declare that this assignment is original and has not been submitted for assessment elsewhere, and acknowledge that the assessor of this assignment may, for the purpose of assessing this assignment: a) Reproduce this assignment and provide a copy to another member of Faculty; and/or b) Communicate a copy of this...

005_y4zaapo-bf4utvaw.pdf 005_modaapo-o1bvksgy.xls

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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