Syllabus

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.