To solve the first three parts of the problem, we need to perform the following steps:
Data Cleaning and Preparation: Extract the data from the table and organize it into a usable format, such as a list of tuples or a pandas DataFrame. Ensure that all numerical values are correctly parsed and any errors in the data are corrected.
Data Analysis: Calculate basic statistics such as mean, median, and standard deviation for both the online trailer views and the box office gross. This will help in understanding the distribution and central tendency of the data.
Correlation Analysis: Compute the correlation coefficient between the online trailer views and the box office gross to determine the strength and direction of the relationship between these two variables.
The mean of the trailer views is calculated as:
\[
\text{Mean Trailer Views} = 21.9535
\]
The median of the trailer views is:
\[
\text{Median Trailer Views} = 10.344
\]
The standard deviation of the trailer views is:
\[
\text{Standard Deviation of Trailer Views} = 23.6480
\]
The mean of the box office gross is:
\[
\text{Mean Box Office Gross} = 28.8983
\]
The median of the box office gross is:
\[
\text{Median Box Office Gross} = 12.43
\]
The standard deviation of the box office gross is:
\[
\text{Standard Deviation of Box Office Gross} = 43.1315
\]
The correlation coefficient between the trailer views and the box office gross is:
\[
\text{Correlation} = 0.7957
\]
This indicates a strong positive correlation between the number of trailer views and the box office gross.
- Mean Trailer Views: \(\boxed{21.9535}\)
- Median Trailer Views: \(\boxed{10.344}\)
- Standard Deviation of Trailer Views: \(\boxed{23.6480}\)
- Mean Box Office Gross: \(\boxed{28.8983}\)
- Median Box Office Gross: \(\boxed{12.43}\)
- Standard Deviation of Box Office Gross: \(\boxed{43.1315}\)
- Correlation between Trailer Views and Box Office Gross: \(\boxed{0.7957}\)
Answered
