ENS6152 Steel Design Assignment Help
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Descriptive statistics of Gross Revenue:
Column1 

Mean 
65.92714286 
Standard Error 
12.74835205 
Median 
26.82 
Mode 
#N/A 
Standard Deviation 
111.8663352 
Sample Variance 
12514.07696 
Kurtosis 
11.76090225 
Skewness 
3.24359001 
Range 
651.6 
Minimum 
0.67 
Maximum 
652.27 
Sum 
5076.39 
Count 
77 
This analysis tells that average gross revenue is 65.92. the standard deviation of this distribution is large so we can say that there is more fluctuation in the data.
Column1 

Mean 
2460.052 
Standard Error 
117.8053 
Median 
2720 
Mode 
3003 
Standard Deviation 
1033.737 
Sample Variance 
1068613 
Kurtosis 
0.87365 
Skewness 
0.23422 
Range 
3658 
Minimum 
653 
Maximum 
4311 
Sum 
189424 
Count 
77 
The data of theatres shows that the average value is 3003 and the standard deviation is 1033. It is negatively skewed data from skewness measure which is 0.234.
Column1 

Mean 
54.71429 
Standard Error 
2.049445 
Median 
56 
Mode 
81 
Standard Deviation 
17.98381 
Sample Variance 
323.4173 
Kurtosis 
0.99233 
Skewness 
0.061818 
Range 
67 
Minimum 
22 
Maximum 
89 
Sum 
4213 
Count 
77 
The mean of a meteoritic score is 54.71. it is positively skewed data. Only 16 movies are of the category in a robot. Their average metacritique ranking is 54.66667 which shows that it is very close to the on an average metacritique ranking.
C. Ans
Boxandwhisker plot for the distribution of the gross revenue:
D. Ans
Correlation between a rating of a film and the revenue
0.160167647
They are positively correlated so we can say that both the data is in the same direction. If one is increasing then another will also increase.
Column1 

Largest(1) 
4311 
Smallest(1) 
653 
Confidence Level(90.0%) 
196.16365 
No of action films analyses: = 13
Mean of their gross income = 228.38 millions
P value for the liklyhood test = 0.003102892 . so it is very less probable that film earn this much amount.
Regression output of Y
SUMMARY OUTPUT 

Regression Statistics 

Multiple R 
0.781191 

R Square 
0.61026 

Adjusted R Square 
0.555433 

Standard Error 
58.77616 

Observations 
76 

ANOVA 


df 
SS 
MS 
F 
Significance F 

Regression 
8 
367832.9 
45979.11 
15.21073 
1.81E12 

Residual 
68 
234915.3 
3454.637 

Total 
76 
602748.2 





Coefficients 
Standard Error 
t Stat 
Pvalue 
Lower 95% 
Upper 95% 
Lower 95.0% 
Upper 95.0% 
Intercept 
159.867 
32.93921 
4.85339 
7.42E06 
225.596 
94.1376 
225.596 
94.1376 
4291 
0.047216 
0.00852 
5.541532 
5.27E07 
0.030214 
0.064218 
0.030214 
0.064218 
59 
1.354561 
0.418749 
3.234777 
0.001881 
0.518959 
2.190162 
0.518959 
2.190162 
1 
65.2928 
20.40998 
3.199063 
0.002095 
24.56532 
106.0203 
24.56532 
106.0203 
1 
46.23357 
26.21074 
1.763917 
0.082238 
6.06914 
98.53627 
6.06914 
98.53627 
0 
13.34658 
31.99987 
0.417082 
0.677932 
50.5082 
77.20133 
50.5082 
77.20133 
0 
12.27422 
25.26018 
0.485912 
0.628592 
38.1317 
62.68012 
38.1317 
62.68012 
0 
13.32961 
23.82147 
0.559563 
0.577616 
34.2054 
60.86461 
34.2054 
60.86461 
0 
0 
0 
65535 
#NUM! 
0 
0 
0 
0 
The regression line found In the previous examples tells the relationship between Y Gross Revenue in Millions of US$ and X Number of theatres. P value in this test is equal to 5.71E11. This less than 0.05 so we can say that we need to accept the null hypothesis. The intercept of the coefficient is 93.6278 and the standard error in this 75.2322.
The regression line in above case can be written as
Y = 159.867 + 0.047216 X_{1} + 1.354561 X_{2}+ 65.2928 X_{3} + 46.23357 X_{4} + 13.34658 X_{5} + 12.27422 X_{6} + 13.32961 X_{7} + 0 X_{8}
It is a relationship between Gross Revenue in Millions of US$ and other variables. The gross revenue can be predicted from the number of theaters and other variables. The intercept part is 159.867. it is negative so we can say that in the case where all variables are 0 then it shows the negative gross income so there is a loss in this business. The coefficient of last variable is 0 , it means that it does not affect the gross income.
R Square 
0.61026 
Adjusted R Square 
0.555433 
The adjusted R squire is a modified version of R squire. In the prediction of the output we modified the relation and it shows that the updated r squire. If the adjusted R squire is larger than it means that the expected value is larger than the actual one.
K. Ans
Since p value is less than 0.05 in all cases except X_{3}, X_{4}, X_{5} so we can say that overall modal satisfying the required significance except these variables.
L. Ans
There are eight independent variables which effect the gross revenue in this regression modal but since the coefficient of X_{8} is 0 so we can say that except thriller all other factors effects the gross profit.
It is given that
Y gross profit
X1 Metacritique score of 30
X2 Shows in 4,000 theatres
X3 Not a sequel or a reboot
Regression analysis result
SUMMARY OUTPUT 

Regression Statistics 

Multiple R 
0.767026 

R Square 
0.588329 

Adjusted R Square 
0.571176 

Standard Error 
58.70521 

Observations 
76 

ANOVA 


df 
SS 
MS 
F 
Significance F 

Regression 
3 
354614.5 
118204.8 
34.29904 
7.04E14 

Residual 
72 
248133.7 
3446.302 

Total 
75 
602748.2 





Coefficients 
Standard Error 
t Stat 
Pvalue 
Lower 95% 
Upper 95% 
Lower 95.0% 
Upper 95.0% 
Intercept 
158.8 
30.8676 
5.14457 
2.23E06 
220.334 
97.267 
220.334 
97.267 
4291 
0.051576 
0.007616 
6.771887 
2.9E09 
0.036393 
0.066759 
0.036393 
0.066759 
59 
1.447145 
0.385132 
3.757532 
0.000346 
0.679399 
2.214892 
0.679399 
2.214892 
1 
66.64747 
19.42855 
3.430388 
0.001001 
27.91736 
105.3776 
27.91736 
105.3776 
Regression line is Y = 158.8 + 0.051 X_{1}+1.447 X_{2}+ 66.64 X_{3}
Predicted Y =158.8 + 0.051 x 30+1.447 x 4000+ 66.64 x 0
Y = 5601.65
Following graph shows the connection among these three variables. The curves shows that the nonlinear distribution of Gross profit, the theatres. The graph of metacritique shows the linear distribution or we can say that it is closed to linear distribution.
The above analysis tells very much information about the movies interest Australia. We can see that only 16 movies are of category reboot. On other side 15 movies are of comedy category their average metacritique ranking is 51.66667. it is very less in the case of metacritique ranking of the movies which are under reboot category. So it directly tells that most of the people taking interest in the movies of reboot category. This interest is larger than the movies of action categories. There are 14 movies are of categories in action so we can see that the average of the metacritique ranking of these movies is 52.71429. it is less than the average ranking. The average gross income of action movies is 156.37. it is larger than the average income of all type of the movies so we can try to analyze this interest also.