svetlanagruzdeva/wnba-project

Revision of the concepts of Inferential Statistics using a dataset containing data from WNBA players.

Lab | Inferential Statistics Review

Introduction

The objective of this lab is to review the concepts of Inferential Statistics that you learned during this week. We will review them by using a dataset containing data from WNBA players and imagining that you want to contribute to heated family discussions over various topic related to basketball.

The question that we will try to resolve through statistics are the following:

• Your grandmother says that your sister couldn’t play in a professional basketball league (not only the WNBA, but ANY professional basketball league) because she’s too skinny and lacks muscle.
• Your sister says that most female professional players miss their free throws.
• Your brother-in-law heard on the TV that the average assists among NBA (male) and WNBA (female) players is 52 for the 2016-2017 season. He is convinced this average would be higher if we only considered the players from the WNBA.

Getting Started

This lab has three parts. Start with 1.-Data-Cleaning.ipynb, then 2.-Exploratory-Data-Analysis.ipynb and finally 3.-Inferential-Analysis.ipynb.

Deliverables

• The 3 notebooks with your code and comments.

Submission

Upon completion, add your deliverables to git. Then commit git and push your branch to the remote.

Resources

WNBA Player Stats 2017