TV Movie Ratings Case Study (g-2)

Statistical Analysis with p-values

Analysis Scope: CBC Network movies (30 observations)
Dependent Variable: Rating (— avg)
Available Variables: Fact, Stars, Previous Rating, Competition
Status: 🔧 Uses sample variances for t-tests; df-based critical values; real OLS regression with p-values (jStat)

The Case and the Questions

The Network has collected data on the ratings of their TV movies. They have kept track of whether the movies had stars, if the plots were based on real-life situations, what the ratings were for the lead-in show to the movie and what the ratings were for the competition at the same time.

You can generate a new data set, then download it to do your own analysis. You can also use the two analysis tabs to use the metrics calculated by the tool. The executives have the following questions:

Question 1: Should the network choose to hire stars to improve their ratings or not?

Question 2: Should the network choose plot-lines based on real life situations or not?

Question 3: Which strategy increases ratings more - hiring stars or using reality-based plot-lines?

Question 4 [Advanced]: Which single factor should the network prioritize as their primary programming strategy?

Note: Two variables are binary (Stars, Fact) and two are continuous (Previous Rating, Competition). The tool computes a proper multiple regression to compare their partial effects.

A/B Comparison using One-Tailed T-Tests

Test whether one group gets higher ratings than another using one-tailed t-tests (equal variances assumed, 95% confidence). Uses sample variances and df-based critical values.

Select Comparison:

Multiple Linear Regression Analysis

Select which independent variables to include in your regression model:

Selected: Fact, Stars, Previous Rating, Competition (4 variables)