🗓️ Week 05 - Vectorization + Functions, Linear Regression in Practice

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This week starts with vectorization (moved from Week 4 to make room for the proposals): operating on whole vectors at once instead of looping. Then we write our own functions, and on Tuesday apply both to fitting and interpreting linear regression models.

Date	Time	Format	Topic
Thu, Oct 22	1:30-3:05 pm	Lecture	Vectorization + Functions
Tue, Oct 27	9:50-10:55 am	DS	Practice: Vectorization + Functions
Tue, Oct 27	1:30-3:05 pm	Lecture	Linear regression in practice + AI audit #1

Solve the Tuesday-morning DS on your own without generative AI and upload your PDFs to Canvas. Printing is now optional. This week the 1-point discussion check is on Tuesday afternoon: you swap laptops with a classmate and check each other’s DS, so bring your laptop, charged. Thursday starts with the DS 4 discussion check: bring your DS 4 PDF, printed or on your laptop.

🤖 AI & Learning This Week

AI status this week: No AI for the DS. AI audit #1 on Tuesday (AI output is provided, no account needed).

Why: A regression that runs is not a regression that is right. This week you first see AI output with plausible-looking mistakes.

This week:

AI audit #1 (Tuesday lecture): you get a regression analysis “written by an AI” with planted problems (an unchecked assumption, a misread coefficient, an overreaching conclusion). In small groups, find and fix them, then discuss how you found them.
Habit to build: check residual plots and the units of every coefficient before believing any interpretation.

See the AI Use Policy for the full rules.

👨‍🏫 Lecture Slides

Thu, Oct 22 (Lecture): Vectorization + Functions
Tue, Oct 27 (DS): DS 5: Vectorization + Functions
Tue, Oct 27 (Lecture): DS 5 Check + Linear Regression in Practice + AI audit #1

💻 Hands-on: Intro to R

Lesson 9: Vectorization
Lesson 10: Functions Explained
Lesson 11: Regression in Practice: practice for Tuesday’s lecture, with your own year of data.

Lessons 9 and 10 are the DS.