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Next Steps

Regression Modeling

  • Explore linear and logistic regression techniques

  • Great for analyzing trends, predictions, and relationships between variables

Data Visualization

  • Create clear, customizable graphs

  • Start with basic plots like scatter plots and bar charts

  • Learn to adjust themes, colors, and labels for readability

Working with Real-World Data

  • Practice importing and analyzing .csv and other data files

  • Use datasets from Kaggle, government databases, or your own projects

Statistical Analysis and Inference

  • Go deeper with concepts like p-values, confidence intervals, and hypothesis testing

  • Learn how to run t-tests and chi-squared tests

Machine Learning Basics

  • Explore predictive modeling and classification

  • Try out algorithms like decision trees and k-nearest neighbors

  • Use libraries like caret or randomForest to begin experimenting

Start a research project on a topic you're passionate about!

Research projects that Ethan has done in the past:

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Programs + Competitions

Wharton Moneyball Academy

  • A summer program for high school students interested in sports analytics

  • Teaches data science, R programming, and statistical modeling

  • Hosted by the Wharton School at the University of Pennsylvania

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Start your own Sports Analytics Club to share what you've learned! Share this website so others can learn!

Wharton Data Science Competition

  • Great competition to bring to your school!

  • Compete alongside friends 

  • Detailed steps and requirements on their website below 

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NFL Big Data Bowl

  • Annual competition hosted by the NFL for students and professionals

  • Uses real tracking data to solve strategic football questions

  • Winners gain exposure to teams and analysts in the league

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DataCamp Competitions

  • Ongoing challenges in data analysis and visualization

  • Offers feedback, rankings, and learning opportunities

  • Great for practicing in a low-stakes but competitive environment

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Kaggle Competitions

  • World’s largest platform for data science challenges

  • Ranges from beginner-friendly to highly advanced problems

  • A great place to build your portfolio and learn from others’ code

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