1. We made a scatter plot to see if there was a correlation between age and the amount of money spent when going out to the movie theaters. By looking at the scatter plot you can see that there appears to be no correlation between the two variables. When calculating to see if there is a significant linear correlation using the given correlation coefficient and the significance level of 0.05, it supports our claim that there is no linear correlation.
2. Linear Regression
r =(+/) 0.730 n= 93
Critical Values: r<0.730
ŷ = 17.21 + 0.057x
Conclusion: No linear correlation
3. Hypothesis test: We wanted to compare the average amount of money spent when going out to the movie theaters compared to money spent on streaming plat forms. We did two independant simple random samples, one of 10 people who went out to the movie theaters, and one of 14 people who used streaming platforms.
We used a 0.05 significance level to test the claim that the mean amount of money spent on streaming platforms was greater than the mean amount of money spent when going out to the move theaters.
Money Spent going Out to Theater Money spent Streaming
X1= $21.80 X2= $23.40
S1= 14.8 S2= 17.3
n1= 10 n2= 14
2SampleTTest
H0:μ1 = μ2
H1:μ1 < μ2
ttest=0.243
Pvalue:0.4051
Conclusion: Fail to reject
The sample data support the claim that the mean amount of money spent on streaming platforms was greater than the mean amount of money spent when going out to the movie theaters.
Simple linear regression results:Dependent Variable: Money spent at theaters Independent Variable: Age Money spent at theaters = 17.210644 + 0.057199899 Age Sample size: 93 R (correlation coefficient) = 0.03622037 Rsq = 0.0013119152 Estimate of error standard deviation: 17.930498 Parameter estimates:
Analysis of variance table for regression model:

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