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Part 2

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Create a line graph of the monthly average ratings for CBC for the year. Note that there are multiple ratings data for the months; you will need to calculate an average for each month first, and then plot the averages. After you create the graph, fit a linear trend line, displaying the formula and the r-squared. Explain to the executives if you can use this time series data to forecast the ratings of upcoming months. How accurate can you expect this forecast to be?
3. Should the CBC hire stars for their movies? To answer this question, run a hypothesis test to see if there is a significant difference between the ratings of movies with stars versus movies without stars. Use the data for CBC movies only. Use 95% confidence. Answer the following:
a. What are the null and alternative hypotheses (state in full sentences)?
b. Run the test using Excel and include the output table. Use a t-test assuming equal variances.
c. What is your recommendation to the executives? Justify your answer referring to the relevant figures.
4. Run a multiple regression where the dependent variable is ratings and the independent variables are star and fact. Use data from CBC only. CBC Management has several questions:
a. Which has more impact on a movie’s rating: Being fact-based or having one star? How much does each of these factors change the ratings?
b. How well does this regression analysis explain the ratings? Justify your answers referring to the relevant figures.
c. Are either, both, or neither of the independent variables significantly related to the ratings at 95% confidence? Justify your answers referring to the relevant figures.

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