UW–Madison STAT 240: Data Science Modeling I
STAT 240 is UW–Madison's R-based introduction to data science — data wrangling with the tidyverse, visualization, probability foundations, statistical inference, and regression, all through case studies and R Markdown reports. It anchors the booming data science major and certificate.
Fennie is independent and not affiliated with University of Wisconsin–Madison. This is an unofficial study guide.
Build my STAT 240 study planWhat makes it hard
Two skills run in parallel: programming in R, which non-coders find genuinely foreign in the early weeks, and statistical reasoning, which arrives mid-semester just as the coding gets comfortable. The case-study format means assignments are multi-step analyses rather than discrete exercises, so falling behind in either skill stalls entire assignments.
What you'll cover
- • R and the tidyverse
- • Data wrangling and visualization
- • Probability and distributions
- • Statistical inference basics
- • Simple linear regression
- • Reproducible reports in R Markdown
The STAT 240 study guide
How to study for UW–Madison STAT 240, step by step.
- 1
Run every line of example code yourself
Reading R is not learning R. Execute each example, change it, break it, and predict what changes — that loop is how the tidyverse's verbs become vocabulary instead of syntax to look up.
- 2
Practice wrangling on fresh datasets weekly
The course's core skill is making real data usable — filtering, joining, reshaping. Repeating those moves on data you haven't seen builds the transfer the case-study assignments demand.
- 3
Don't let the statistics arrive unannounced
Probability and inference land mid-semester just as the coding feels comfortable. Treat the statistical concepts as a parallel track from the start, not an interruption to the programming.
- 4
Connect every computation to a plain-English claim
Each interval, test, or model coefficient should end in a sentence about the data's actual context. The case-study reports grade interpretation, and the habit cements the concepts.
- 5
Keep both tracks moving with Fennie
Upload your STAT 240 syllabus and Fennie's Daily Plan paces R practice and statistical-concept review in parallel, synced to assignment and exam dates, with quizzes generated from your actual course materials. Free to start.
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How Fennie helps with STAT 240
Fennie's Daily Plans run STAT 240's two skill tracks in parallel — R practice scheduled steadily, statistical concepts reviewed before the mid-semester pivot needs them — paced to case-study deadlines. Chat explains what your tidyverse pipeline actually does, step by step, and why an inference procedure applies to the case at hand.
FAQ
Is STAT 240 at UW–Madison hard?
It's two courses in one — R programming and statistical reasoning — and the difficulty depends on which you arrive without. Non-coders find the early weeks steep; everyone meets real statistics mid-semester. Steady parallel practice in both keeps it very manageable.
Do I need programming experience for STAT 240?
No — it teaches R from scratch. But true beginners should budget extra practice in the first month, because the case-study assignments assume working R fluency surprisingly quickly.
What's the difference between STAT 240 and STAT 301?
STAT 240 is the R-based data science route, built around wrangling and case studies, and it anchors the data science major and certificate. STAT 301 is a conventional introductory statistics methods course. Which to take depends on your program — check your degree requirements.
Pass STAT 240 with a plan, not a cram
Upload your STAT 240 materials and Fennie generates a Daily Plan paced to your deadline — plus chat, flashcards, and quizzes built from the actual course content.
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