Schedule

This page contains an outline of the course schedule and all relevent course materials. The schedule is subject to change as the semester progresses. Updates will be posted here. Exam dates and project due dates will not change.

Many thanks to Dr. Mine Γ‡etinkaya-Rundel for sharing course materials.

Day Topic Prepare In-class Materials Due Date
Thur, May 16 Lec: Welcome to STA 199 πŸ“— r4ds - intro
πŸ“˜ ims - chp 1
πŸ–₯️ slides 00
⌨️ ae 00
πŸ–₯️ slides 01
⌨️ ae 01
no AEs due
Β  Lab 0: Hello, World and STA 199! Β  πŸ’» lab 0 survey due by end of class
Mon, May 20 Lec: Data visualization πŸ“— r4ds - chp 1
πŸŽ₯ Data and visualization
πŸŽ₯ Visualising data with ggplot2
πŸ“˜ ims - chp 4
πŸ“˜ ims - chp 5
πŸŽ₯ Visualizing numerical data
πŸŽ₯ Visualizing categorical data
πŸ–₯️ slides 02
⌨️ ae 02
βœ… ae 02
πŸ–₯️ slides 03
Β 
Β  Lab 1: Data visualization πŸ“— r4ds - chp 2 πŸ’» lab 1
βœ… lab 1
lab 1 due 5/23 by 11:59 PM
Tu, May 21 Lec: Data wrangling πŸ“˜ ims - chp 6
πŸŽ₯ Working with a single data frame
πŸ“— r4ds - chp 3.6-3.7
πŸ“— r4ds - chp 4
πŸ–₯️ slides 04
⌨️ ae 03
βœ… ae 03
πŸ–₯️ slides 05
⌨️ ae 04
βœ… ae 04
Β 
Thur, May 23 Lec: Tidying data πŸŽ₯ Tidying data
πŸ“— r4ds - chp 5
πŸ–₯️ slides 06
⌨️ ae 05
βœ… ae 05
AEs 2-5 due 5/26 by 11:59 PM
Β  Lab 2: Data wrangling πŸŽ₯ Grammar of data wrangling πŸ’» lab 2
βœ… lab 2
lab 2 due 5/26 by 11:59 PM
Mon, May 27 No class - Memorial Day holiday Β  Β  Β 
Tu, May 28 Lec: Joins and data types πŸ“— r4ds - chp 19.1-19.3
πŸŽ₯ Data types
πŸŽ₯ Data classes
πŸ“— r4ds - chp 16
πŸ–₯️ slides 07
⌨️ ae 06
βœ… ae 06
πŸ–₯️ slides 08
⌨️ ae 07
βœ… ae 07
Β 
Thur, May 30 Lec: Exam review πŸŽ₯ Importing data
πŸŽ₯ Recoding data
πŸ“— r4ds - chp 7
πŸ“— r4ds - chp 17.1 - 17.3
πŸ–₯️ slides 09
πŸ“ exam 1 review
βœ… exam 1 review
AEs 6-7 due 6/2 by 11:59 PM
Β  Lab 3: Data tidying and joining πŸŽ₯ Working with multiple data frames πŸ’» lab 3
βœ… lab 3
lab 3 due 6/2 by 11:59 PM
Mon, June 3 Lec: Exam 1 - In-class + take-home released and importing data πŸŽ₯ Functions
πŸŽ₯ Iteration
πŸ“— r4ds - chp 25.1 - 25.2
βœ… Exam 1 in class key
πŸ–₯️ slides 10
⌨️ ae 08
βœ… ae 08
⌨️ ae 09
Exam 1 take-home due 6/6 at 11:59 PM
βœ… Exam 1 in class key
Β  Lab: Project milestone 1 - Working collaboratively Β  πŸ““ project milestone 1 due 6/6 by 11:59 PM
Tu, June 4 Lec: Data science ethics and intro to modeling πŸŽ₯ Misrepresentation
πŸŽ₯ Data privacy
πŸŽ₯ Algorithmic bias
πŸ“• mdsr - chp 8
πŸŽ₯ Alberto Cairo - How charts lie
πŸŽ₯ Joy Buolamwini - How I’m fighting bias in algorithms
πŸŽ₯ The language of models
πŸ“˜ ims - chp 7.1
πŸ–₯️ slides 13
πŸ–₯️ slides 14
⌨️ ae 10
βœ… ae 10
πŸ–₯️ slides 15
Β 
Thur, June 6 Lec: Linear regression πŸŽ₯ Fitting and interpreting models
πŸŽ₯ Modeling nonlinear relationships
πŸ“˜ ims - chp 7.2
πŸŽ₯ Models with multiple predictors
πŸŽ₯ More models with multiple predictors
πŸ“˜ ims - chp 8.1-8.2
πŸ–₯️ slides 15 recap
⌨️ ae 11
βœ… ae 11
πŸ–₯️ slides 16
⌨️ ae 12
βœ… ae 12
AEs 8-12 due 6/9 by 11:59 PM
Β  Lab 4: Modelling I Β  πŸ’» lab 4
βœ… lab 4
lab 4 due 6/9 by 11:59 PM
Mon, June 10 Lec: Linear regression with multiple predictors II πŸ“˜ ims - chp 8.3-8.5 πŸ–₯️ slides 17
⌨️ ae 13
βœ… ae 13
Β 
Β  Lab: Project milestone 2 - Project proposals Β  πŸ““ project milestone 2 due 6/13 by 11:59 PM
Tu, June 11 Lec: Model selection and overfitting πŸŽ₯ Logistic regression
πŸŽ₯ Prediction and overfitting
πŸ“˜ ims - chp 9
πŸ–₯️ slides 18
πŸ–₯️ slides 19
⌨️ ae 14
βœ… ae 14
Β 
Thur, June 13 Lec: Quantifying uncertainty with bootstrap intervals πŸŽ₯ Quantifying uncertainty
πŸŽ₯ Bootstrapping
πŸ“˜ ims - chp 12
bootstrap exploration
πŸ–₯️ slides 20
⌨️ ae 15
βœ… ae 15
AEs 13-15 due 6/16 by 11:59 PM
Β  Lab 5: Modeling II Β  πŸ’» lab 5
βœ… lab 5
lab 5 due 6/16 by 11:59 PM
Mon, June 17 Lec: Making decisions with randomization tests and exam review πŸ“˜ ims - chp 11 πŸ–₯️ slides 21
⌨️ ae 16
βœ… ae 16
Β 
Β  Lab: Exam 2 review Β  πŸ“ exam 2 review
βœ… exam 2 review
Β 
Tu, June 18 Lec: Communicating data science results effectively πŸŽ₯ Tips for effective data visualization
πŸ“˜ ims - chp 6
πŸ“— r4ds - chp 10
πŸŽ₯ Doing data science
πŸ–₯️ slides 23
⌨️ ae 17
βœ… ae 17
⌨️ ae 18
teammate evaluation 1 due 6/18 at 11:59 PM
Wed, June 19 Juneteenth holiday Β  Β  Β 
Thur, June 20 Lec: Exam 2 - In-class + take-home released and Shiny app overview Β  πŸ–₯️ slides 24
⌨️ ae 19
AEs 16-19 due 6/23 by 11:59 PM
Take-home exam 2 due SAT 6/22 at 11:59 PM
Β  Lab: Project milestone 3 - Peer review Β  πŸ““ project milestone 3 due by end of class
Mon, June 24 Project work day: No lecture Β  Β  Β 
Β  Lab: Project milestone 4 - Project presentations Β  πŸ““ project milestone 4 Project write-up due 6/25 at 11:59 PM
teammate evaluation 2 due 6/25 at 11:59 PM
Β  Β  Β  Β  Β