This is my week 7 data dive where I conduct hypothesis testing using Fisher Significance Framework (FG% and shot distance) and Neyman-Pearson Framework (comparing FG% and position)

This is my week 6 data dive where I created two calculated metrics: Distance-Adjusted Efficiency (DAE) and Shooting Efficiency (SE). I then compared DAE to Average Shot Distance and SE to FG% by using correlation matrices confidence intervals, and visual plots.

this is my resubmission of the week 4 data dive based on the feedback provided by my TA including hiding libraries using include = FALSE and elaborating how the analysis done will impact future analysis.

This week, I dove into the data documentation for the NBA shooting analytics dataset to have better clarity on the data being presented.

Analyzing three point attempt samples analyzing the significance of outliers.

This is my submission for the week3datadive where I analyze shooting efficiencies grouped by position, teams, and age. I also analyze team roster construction by analyzing the combinations of teams and positions to understand how teams are building their rosters to maximize offensive success.

The analysis done is comparing NBA shooting statistics and distance, specifically how the different types of shots attempted by players and team impacts efficiency and if there is a difference in efficiency by distance among positions.