Summer Data Science Camps

In this week, students learn how raw information becomes insight. They collect and organize real-world data, write code in R using the industry-standard Posit Cloud, and build visualizations that reveal patterns and relationships. Along the way, they practice asking stronger statistical questions, not just “What does this show?” but “What does this actually mean?” Students also explore digital ethics, data privacy, and responsible sharing, building technical skill alongside thoughtful judgment. By the end of the week, they’re not just reading charts. They’re creating them, interpreting them, and explaining their conclusions with evidence.

In Week 2, students focus on understanding and using data. Students explore datasets using mathematical concepts like mean, median, variability, and distribution to understand what’s typical, what’s unusual, and how groups compare. They learn to analyze subsets of data, interpret boxplots, and support their conclusions with numerical evidence. This is where students get to build concrete proof and practice backing up claims with math, communicating statistical findings clearly and responsibly. By the end of the week, students can compare data with confidence and explain their reasoning step by step.

In Week 3, students explore uncertainty. They clean and prepare real datasets, analyze categorical relationships, and calculate conditional probabilities. They build simulations to test “what if” scenarios and use various techniques to understand possible outcomes. Students examine fairness and risk, applying probability reasoning to real decision-making situations. By the end of the week, they’ve developed tools to make informed predictions and evidence-based computations in uncertain situations.