uppose an online media streaming company is interested in building a movie recommendation system. the website maintains data on the movies in their database (genre, length, cast, director, budget, etc.) and additionally collects data from their subscribers ( demographic information, previously watched movies, how they rated previously watched movies, etc.). the recommendation sys- tem will be deemed successful if subscribers actually watch, and rate highly, the movies recommended to them. should the company use the adjusted r2 or the p-value approach in selecting variables for their recommendation system?

Answer

It is more appropriate to use the adjusted r2 approach, since it measures the goodness of fit of a regression model that includes multiple variables, taking into account the number of variables used, while the p-value approach only measures the significance of each individual variable. In this case, since the recommendation system will involve multiple variables (genre, length, cast, director, budget, demographic information, previously watched movies, how they rated previously watched movies, etc.), the adjusted r2 approach would be a more suitable method for selecting variables.

What is the purpose of the recommendation system? A: The recommendation system will be deemed successful if subscribers actually watch, and rate highly, the movies recommended to them.
What data does the website collect? A: Demographic information, previously watched movies, how they rated previously watched movies, etc.
What is the difference between adjusted r2 and p-value approaches?
Which approach is more appropriate for selecting variables for the recommendation system?