Statistics 131a: Statistical Methods for Data Science
UC Berkeley, Fall 2024
Announcements ๐ฃ
Midterm 2 walkthrough video posted to bcourses.
Lab 10 is due Friday, 11/22 at midnight. Posted before Tuesdayโs lab section.
HW5 is due Monday, 11/25 at midnight.
Schedule ๐
Week 13
Fri Nov 22: | Lecture 22 k-means clustering | |
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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 |
Worksheet Abridged slides for live notes |
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 20 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) |
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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) |
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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) |
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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) |
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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) |
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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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