Statistics 131a: Statistical Methods for Data Science
UC Berkeley, Fall 2024
Announcements 📣
The final exam is Thursday, December 19th at 3pm in GPBB 100.
Schedule 📅
Week 16
| Fri Dec 13: | Lecture FP3 Final prep lecture 3 |
Practice problems on bcourses |
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| Wed Dec 11: | Lecture FP2 Final prep lecture 2 |
Practice problems on bcourses |
| Mon Dec 9: | Lecture FP1 Final prep lecture 1 |
Slides Annotated slides Practice problems on bcourses |
Week 15
| Fri Dec 6: | Lecture 24b More on decision trees, bagging, and random forests |
Slides Worksheet |
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| Thu Dec 5: | Section 26 Wrap up k-means and PCA. If time, decision trees. | |
| Wed Dec 4: | Lecture 24a Decision trees, bagging, and random forests |
Slides Worksheet |
| Tue Dec 3: | Section 25 k-means and PCA |
Lab 11 (DataHub) Lab 11 (GitHub) |
| Mon Dec 2: | Lecture 23b More on PCA |
Slides Worksheet Lecture code (DataHub) Lecture code (GitHub) |
Week 14
| Fri Nov 29: | Holiday (Thanksgiving Break) | |
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| Thu Nov 28: | Holiday (Thanksgiving Break) | |
| Wed Nov 27: | Holiday (Thanksgiving Break) | |
| Tue Nov 26: | Section NA No section today! | |
| Mon Nov 25: | Lecture 23a Principal component analysis (PCA) |
Slides Worksheet Lecture code (DataHub) Lecture code (GitHub) |
Week 13
| Fri Nov 22: | Lecture 22 k-means clustering |
Slides Worksheet |
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| Thu Nov 21: | Section 24 Logistic regression and classification error metrics | |
| Wed Nov 20: | Lecture 21 A brief overview of statistical methods |
Slides Worksheet |
| Tue Nov 19: | Section 23 Logistic regression and classification error metrics |
Lab 10 (DataHub) Lab 10 (GitHub) |
| Mon Nov 18: | Lecture 20b More on classification error metrics |
Slides Worksheet |
Week 12
| Fri Nov 15: | Lecture 20a Classification error metrics |
Slides Worksheet |
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| Thu Nov 14: | Section NA Relax after midterm! No section. | |
| Wed Nov 13: | Lecture MT2 Midterm 2 (in class) |
Seating map |
| Tue Nov 12: | Section 21 Midterm 2 Review |
Annotated slides Worksheet |
| Mon Nov 11: | Holiday (Veterans Day) |
Week 11
| Fri Nov 8: | Lecture MT2P Midterm 2 Prep Lecture | |
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| Thu Nov 7: | Section 20 Midterm 2 Review | |
| Wed Nov 6: | Lecture 19b More on logistic regression |
Slides Annotated slides Worksheet Lecture code (DataHub) Lecture code (GitHub) |
| Tue Nov 5: | Section 19 Linear probability models |
Lab 9 (DataHub) Lab 9 (GitHub) |
| Mon Nov 4: | Lecture 19a Logistic regression |
Slides Annotated slides Worksheet Lecture code (DataHub) Lecture code (GitHub) |
Week 10
| Fri Nov 1: | Lecture NA No lecture today | |
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| Thu Oct 31: | Section 18 Review of regression and HW4 Help | |
| Wed Oct 30: | Lecture 18 Linear probability models (LPMs) |
Slides Annotated slides Worksheet Lecture code (DataHub) Lecture code (GitHub) |
| Tue Oct 29: | Section 17 Cross-validation |
Lab 8 (DataHub) Lab 8 (GitHub) |
| Mon Oct 28: | Lecture 17 Cross-validation |
Slides Worksheet |
Week 9
| Fri Oct 25: | Lecture 16c Interactions |
Slides Annotated slides Worksheet Lecture code (DataHub) Lecture code (GitHub) |
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| Thu Oct 24: | Section 16 Wrap up Lab 7, Review polynomial terms + categorical covariates | |
| Wed Oct 23: | Lecture 16b Categorical covariates |
Slides Annotated slides Worksheet Lecture code (DataHub) Lecture code (GitHub) |
| Tue Oct 22: | Section 15 Fitting linear regression (OLS) models |
Lab 7, Part A (DataHub) Lab 7, Part A (GitHub) |
| Mon Oct 21: | Lecture 16a Polynomial terms |
Slides Annotated slides Worksheet Lecture code (DataHub) Lecture code (GitHub) |
Week 8
| Fri Oct 18: | Lecture 15 Closeness of fit |
Slides Worksheet Lecture code (DataHub) Lecture code (GitHub) |
|---|---|---|
| Thu Oct 17: | Section 14 More on multiple testing + HW3 Help |
Lab 6 (DataHub) Lab 6 (GitHub) |
| Wed Oct 16: | Lecture 14 Uncertainty in regression and multiple regression |
Slides Worksheet Lecture code (DataHub) Lecture code (GitHub) |
| Tue Oct 15: | Section 13 Multiple testing via simulation |
Lab 6 (DataHub) Lab 6 (GitHub) |
| Mon Oct 14: | Lecture 13 Correlation and simple linear regression |
Slides Worksheet Lecture code (DataHub) Lecture code (GitHub) |
Week 7
| Fri Oct 11: | Lecture 12b Power and experiment planning |
Slides Worksheet Lecture code (DataHub) Lecture code (GitHub) |
|---|---|---|
| Thu Oct 10: | Section NA Relax after midterm! No section. | |
| Wed Oct 9: | Lecture MT1 Midterm 1 (in class) |
Seating map |
| Tue Oct 8: | Section 11 Midterm 1 Prep Section | |
| Mon Oct 7: | Lecture MT1P Midterm 1 Prep Lecture |
Annotated worksheet/slides Worksheet/slides |
Week 6
| Fri Oct 4: | Lecture 12a Type I+II errors and multiple testing |
Slides Annotated slides Worksheet Lecture code (DataHub) Lecture code (GitHub) |
|---|---|---|
| Thu Oct 3: | Section 10 More on hypothesis testing |
Lab 5 (DataHub) Lab 5 (GitHub) |
| Wed Oct 2: | Lecture 11b More on hypothesis testing |
Slides (Updated) Worksheet Lecture code (DataHub) Lecture code (GitHub) |
| Tue Oct 1: | Section 9 Intro to hypothesis testing |
Lab 5 (DataHub) Lab 5 (GitHub) |
| Mon Sep 30: | Lecture 11a Intro to hypothesis testing |
Slides Annotated slides Worksheet |
Week 5
| Fri Sep 27: | Lecture 10b More on confidence intervals |
Demo (DataHub) Demo (GitHub) Slides Annotated slides Worksheet Lecture code (DataHub) Lecture code (GitHub) |
|---|---|---|
| Thu Sep 26: | Section 8 Confidence intervals in R |
Lab 4, Part B (DataHub) Lab 4, Part B (GitHub) |
| Wed Sep 25: | Lecture 10a Confidence intervals |
Slides Annotated slides Worksheet Lecture code (DataHub) Lecture code (GitHub) |
| Tue Sep 24: | Section 7 The bootstrap in R |
Lab 4, Part A (DataHub) Lab 4, Part A (GitHub) |
| Mon Sep 23: | Lecture 9 The bootstrap |
Slides Demo (DataHub) Demo (GitHub) Worksheet |
Week 4
| Fri Sep 20: | Lecture 8b More on sampling distributions |
Slides Worksheet |
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| Thu Sep 19: | Section 6 Sampling distributions |
Lab 3 (DataHub) Lab 3 (GitHub) |
| Wed Sep 18: | Lecture 8a Sampling distributions |
Demo (DataHub) Demo (GitHub) Slides Worksheet |
| Tue Sep 17: | Section 5 Wrap up probability exercise and Lab 2 | |
| Mon Sep 16: | Lecture 7 Parallel universes |
Slides Worksheet |
Week 3
| Fri Sep 13: | Lecture 6b More parables and perplexing problems pertaining to probability |
Slides Annotated slides Worksheet |
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| Thu Sep 12: | Section 4 Conceptual review of probability | |
| Wed Sep 11: | Lecture 6a Parables and perplexing problems pertaining to probability |
Slides Worksheet |
| Tue Sep 10: | Section 3 Working with distributions in R |
Lab 2 (DataHub) Lab 2 (GitHub) |
| Mon Sep 9: | Lecture 5 Data from Distributions |
Slides Annotated slides Worksheet Lecture code (GitHub) Lecture code (DataHub) |
Week 2
| Fri Sep 6: | Lecture 4 Distributions of Data |
Slides Worksheet Lecture code (DataHub) Lecture code (GitHub) |
|---|---|---|
| Thu Sep 5: | Section 2 Data munging and plotting with stop-and-frisk |
Lab 1 (DataHub) Lab 1 (GitHub) |
| Wed Sep 4: | Lecture 3 Boxplots and Histograms |
Slides Worksheet Lecture code (DataHub) Lecture code (GitHub) |
| Tue Sep 3: | Section 1 Data munging and plotting with stop-and-frisk |
Lab 1 (DataHub) |
| Mon Sep 2: | Holiday (Labor Day) |
Week 1
| Fri Aug 30: | Lecture 2 Principles of visualization |
Slides Worksheet Lab 0 (HTML w/ DataHub Link) |
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| Wed Aug 28: | Lecture 1 Welcome! |
Slides Worksheet |
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