hermawanhermawan / predicting-box-offices

Explore Disney movie data, then build a linear regression model to predict box office success

PROJECT DESCRIPTION

Since the 1930s, Walt Disney Studios has released more than 600 films covering a wide range of genres. While some movies are indeed directed towards kids, many are intended for a broad audience. In this project, dataSET will be analyzed to see how Disney movies have changed in popularity since its first movie release. Moreover, hypothesis testing will be performed to see what aspects of a movie contribute to its success. This project makes use of pandas to manipulate data and seaborn can make basic plots using Seaborn. We will also employ statistical inference and perform two-sample bootstrap hypothesis tests for difference of means. The dataset used in this project is a modified version of the Disney Character Success dataset from Kelly Garrett.

PROJECT DETAIL

1. The dataset
2. Top ten movies at the box office
3. Movie genre trend
4. Visualize the genre popularity trend
5. Data transformation
6. The genre effect
7. Confidence intervals for regression parameters (i)
8. Confidence intervals for regression parameters (ii)
9. Confidence intervals for regression parameters (iii)
10. Should Disney make more action and adventure movies?