Check out this video from the summer 2020 lectures! Including a guest lecture by Professor Rob Tibshirani.
We will cover the following topics. The last few lectures of the class will discuss some active areas such as reproducibility in the scienes, with some topics still pending to change. This page will be updated throughout the quarter to reflect any updates, including reading material drawn from the Statistical Thinking for the 21st Century textbook.
Wednesday sessions are dedicated to R Labs. R Labs are an important component of the course, and a vital one for the project. The goal is to familiarize students with R’s tools for data analysis. Lectures will be interactive with a focus on learning by example, and assignments will be application-driven. No prior programming experience is needed. Topics covered include basic data structures, File I/O, data transformation and visualization, simple statistical tests, etc, and some useful packages in R. The reading material will be drawn from the R Companion.
| Date | Topic | Reading | Notes |
|---|---|---|---|
| 06/22 | What is statistics? overview of the course Slides | Chapter 1 | |
| 06/24 | Introduction to R tutorials - Slides | R Companion, Sections 1.1 to 1.7 | |
| 06/26 | Visualizing Data Slides | Chapter 4 - An Economist’s Guide to Visualizing Data - Excerpts from Tufte’s book | HW1 released |
| 06/29 | Summarizing data Slides | Chapter 3 |
| 07/01 | R Lab: Data visualization with ggplot2 Slides | R Companion, Sections 3.1 to 3.5 |
| 07/03 | Independence Day celebrated - no class |
| 07/06 | Probability Slides | Chapter 6 | |
| 07/08 | R Lab: Data transformation with dplyr Slides - Code | dplyr vignette | |
| 07/10 | Probability, cont. Slides | Chapter 6 | HW1 due |
| 07/13 | Working with data Slides | Chapter 2 | |
| 07/14 | Extra Session - Probability Review Problems | Slides - Solutions | Practice the problems in advance |
| 07/15 | R Lab Slides - Code | R Companion, Sections 2.1 to 2.7 | Quiz 1 and Project Proposal due, Quiz 2 released |
| 07/17 | Fitting models (central tendency) Slides | Chapter 5 | HW2 due |
| 07/20 | Sampling Slides | Chapter 7 | Add all team members to your Gradescope proposal |
| 07/22 | R Lab Slides - Code | R Companion, Sections 6.1, 6.2, 7.1, 7.2 | |
| 07/24 | Hypothesis testing Slides | Chapter 9 |
| 07/27 | Hypothesis testing, cont. Slides | Chapter 9 | |
| 07/29 | R Lab Slides - Code | R Companion, Sections 8.1, 8.2 - Quiz 2 due, Quiz 3 released | |
| 07/31 | z-scores and Hypothesis testing wrap-up Slides | Section 5.9 and Chapter 9 | HW3 due, HW4 released |
| 08/03 | Modeling categorical relationships Slides | Chapter 12 | |
| 08/05 | R Lab Slides - Code | Quiz 3 due | |
| 08/07 | Modeling continuous relationships Slides | Chapter 13 |
| 08/10 | Doing reproducible research Slides - Guest lecture slides (copyright Rob Tibshirani) - Slides with bonus material - notebook.html - notebook.Rmd Learning Objectives: After this lecture, you should be able to: * Describe the concept of P-hacking and its effects on scientific practice * Describe the concept of positive predictive value and its relation to statstical power Links: * Fivethirtyeight P-hacking demo |
Chapter 32 Simmons et al (available on Canvas) https://www.buzzfeed.com/stephaniemlee/brian-wansink-cornell-p-hacking?utm_term=.gtAVwLX2GM#.fep9L6pw78 |
| 08/12 | R Lab Slides - Code | Quiz 4 due |
| 08/14 | Final Projects Showtime | Last day of class - HW4 due |
Acknowledgments: Thanks and acknowledgments to Kenneth Tay for providing much of the material used for the R Labs.