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, you will analyze data to see how Disney movies have changed in popularity since its first movie release. You will also perform hypothesis testing to see what aspects of a movie contribute to its success.
This project assumes that you can manipulate data using pandas and can make basic plots using Seaborn. You should also be familiar with statistical inference and be able to perform two-sample bootstrap hypothesis tests for difference of means. The prerequisites for this project are Introduction to Linear Modeling in Python and Introduction to Seaborn.
The dataset used in this project is a modified version of the Disney Character Success dataset from Kelly Garrett.
Assistant Professor at University of the Thai Chamber of Commerce
Sirinda is an assistant professor in the School of Science and School of Business. She is the head of a bachelor’s degree program in Big Data Management for the School of Business. She has a Ph.D. degree in Computer Science and Engineering from Pennsylvania State University. Her main interests are data analysis and big data for business.See More