Data Exploration and Analysis

Data Exploration and Analysis

S&DS S2300 (CRN: 30152) | Syllabus

Instructors: Jonathan Reuning-Scherer
Dates: Session B, June 29 - July 31, 2026
Course Mode: Online
Meeting Times: MWF 10.00-11.30
Distributional Requirements: Quantitative Reasoning
Eligibility: Open to pre-college and college students

Online course. This course expands on introductory statistics topics and provides an extensive introduction to the R programming language. A concise review of foundational statistical methods moves into topics such as bootstrapping, permutation tests, multiple regression, ANOVA, ANCOVA, generalized linear models, and logistic regression. All topics emphasize the use of appropriate statistical graphics. This course also builds a strong foundation in R, RStudio, and RMarkdown, including data cleaning, data types, and strategies for handling missing data. Lectures incorporate examples of how AI can support both R coding and data analysis. This is a highly applied course, with lectures and homework focused on performing data analysis and communicating results. Prerequisite: a 1000‑level Statistics course or AP Statistics with a score of 4 or 5. 1 credit. Session B: June 29 – July 31. Tuition: $5,480. Technology Fee: $85.

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