Instructors

  • Assistant Director, Lead Instructor: Ron Yurko (ryurko@andrew.cmu.edu) is a PhD student in the Department of Statistics & Data Science at Carnegie Mellon University. In addition to his statistical methodology research oriented towards applications in genetics and genomics, he is actively involved in statistics in sports research. He is a co-organizer of the annual Carnegie Mellon Sports Analytics Conference and Reproducible Research Competition, and has developed multiple R packages to enable easy access of publicly available data, such as nflscrapR.
  • Assistant Director: Nick Citrone (ncitrone@pittsburghpenguins.com)
  • Teaching Assistant: Pratik Patil (pnp1@andrew.cmu.edu)
  • Teaching Assistant: Beomjo Park (beomjop@andrew.cmu.edu)

Program description

The program will concentrate on statistics and data science methodology with applications in sports. Details regarding program topics are presented below, however this calendar is subject to change. All lecture slides will be available at the Lectures tab, and all lab / demo materials will be available at the Labs tab.

Week 1: June 1 - 5

  • Introduction to the program, department, CMSAC
  • Exploratory data analysis, tidyverse
  • Data visualization, grammar of graphics, ggplot2
  • Using Git and GitHub

Week 2: June 8 - 12

  • More data visualization, heatmaps, density estimation
  • K-means and hierarchical clustering
  • Gaussian mixture models

Week 3: June 15 - 19

  • Linear regression
  • Generalized linear models (GLMs)
  • Model assessment, bias-variance tradeoff

Week 4: June 22 - 26

  • Variable selection
  • Cross-validation
  • Penalized regression, Ridge, LASSO, elastic net
  • Dimension reduction, principal component analysis (PCA)

Week 5: June 29 - July 3

  • To be announced!

Week 6: July 6 - 10

  • Polynomial regression
  • Smoothing splines
  • Additive models
  • Empirical Bayes

Week 7: July 13 - 17

  • Decision trees
  • Random Forests
  • Boosting
  • Neural networks
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