Introduces students to reproducible data management, modeling, and analysis through a practical, hands-on case studies approach. Topics include the use of an integrated statistical computing environment, data wrangling, the R programming language, data graphics and visualization, random variables and concepts of probability, data modeling, and report generation using R Markdown with applications to a wide variety of data to address open-ended questions.
-
Project desciption:
Our goal is to understand the importance of having allstars and MVPs in respect to winning NBA championships. We also want to understand the background of these players. Specifically by looking at draft position, player origin, conference, and even height. We want to see how some of these specific factors relate (if at all) to having success in the NBA, in terms of individual and team accomplishments.
-
Type of hypothesis test:
- Binomial test