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 Γetinkaya-Rundel for sharing course materials.
Day | Topic | Prepare | In-class Materials | Due Date |
---|---|---|---|---|
Thur, May 16 | Lec: Welcome to STA 199 | π r4ds - intro π ims - chp 1 | π₯οΈ slides 00 β¨οΈ ae 00 π₯οΈ slides 01 β¨οΈ ae 01 | no AEs due |
Β | Lab 0: Hello, World and STA 199! | Β | π» lab 0 | survey due by end of class |
Mon, May 20 | Lec: Data visualization | π r4ds - chp 1 π₯ Data and visualization π₯ Visualising data with ggplot2 π ims - chp 4 π ims - chp 5 π₯ Visualizing numerical data π₯ Visualizing categorical data | π₯οΈ slides 02 β¨οΈ ae 02 β ae 02 π₯οΈ slides 03 | Β |
Β | Lab 1: Data visualization | π r4ds - chp 2 | π» lab 1 β lab 1 | lab 1 due 5/23 by 11:59 PM |
Tu, May 21 | Lec: Data wrangling | π ims - chp 6 π₯ Working with a single data frame π r4ds - chp 3.6-3.7 π r4ds - chp 4 | π₯οΈ slides 04 β¨οΈ ae 03 β ae 03 π₯οΈ slides 05 β¨οΈ ae 04 β ae 04 | Β |
Thur, May 23 | Lec: Tidying data | π₯ Tidying data π r4ds - chp 5 | π₯οΈ slides 06 β¨οΈ ae 05 β ae 05 | AEs 2-5 due 5/26 by 11:59 PM |
Β | Lab 2: Data wrangling | π₯ Grammar of data wrangling | π» lab 2 β 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 | π r4ds - chp 19.1-19.3 π₯ Data types π₯ Data classes π r4ds - chp 16 | π₯οΈ slides 07 β¨οΈ ae 06 β ae 06 π₯οΈ slides 08 β¨οΈ ae 07 β ae 07 | Β |
Thur, May 30 | Lec: Exam review | π₯ Importing data π₯ Recoding data π r4ds - chp 7 π r4ds - chp 17.1 - 17.3 | π₯οΈ slides 09 π exam 1 review β exam 1 review | AEs 6-7 due 6/2 by 11:59 PM |
Β | Lab 3: Data tidying and joining | π₯ Working with multiple data frames | π» lab 3 β 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 | π₯ Functions π₯ Iteration π r4ds - chp 25.1 - 25.2 | β
Exam 1 in class key π₯οΈ slides 10 β¨οΈ ae 08 β ae 08 β¨οΈ ae 09 | Exam 1 take-home due 6/6 at 11:59 PM β Exam 1 in class key |
Β | Lab: Project milestone 1 - Working collaboratively | Β | π project milestone 1 | due 6/6 by 11:59 PM |
Tu, June 4 | Lec: Data science ethics and intro to modeling | π₯ Misrepresentation π₯ Data privacy π₯ Algorithmic bias π mdsr - chp 8 π₯ Alberto Cairo - How charts lie π₯ Joy Buolamwini - How Iβm fighting bias in algorithms π₯ The language of models π ims - chp 7.1 | π₯οΈ slides 13 π₯οΈ slides 14 β¨οΈ ae 10 β ae 10 π₯οΈ slides 15 | Β |
Thur, June 6 | Lec: Linear regression | π₯ Fitting and interpreting models π₯ Modeling nonlinear relationships π ims - chp 7.2 π₯ Models with multiple predictors π₯ More models with multiple predictors π ims - chp 8.1-8.2 | π₯οΈ slides 15 recap β¨οΈ ae 11 β ae 11 π₯οΈ slides 16 β¨οΈ ae 12 β ae 12 | AEs 8-12 due 6/9 by 11:59 PM |
Β | Lab 4: Modelling I | Β | π» lab 4 β lab 4 | lab 4 due 6/9 by 11:59 PM |
Mon, June 10 | Lec: Linear regression with multiple predictors II | π ims - chp 8.3-8.5 | π₯οΈ slides 17 β¨οΈ ae 13 β ae 13 | Β |
Β | Lab: Project milestone 2 - Project proposals | Β | π project milestone 2 | due 6/13 by 11:59 PM |
Tu, June 11 | Lec: Model selection and overfitting | π₯ Logistic regression π₯ Prediction and overfitting π ims - chp 9 | π₯οΈ slides 18 π₯οΈ slides 19 β¨οΈ ae 14 β ae 14 | Β |
Thur, June 13 | Lec: Quantifying uncertainty with bootstrap intervals | π₯ Quantifying uncertainty π₯ Bootstrapping π ims - chp 12 bootstrap exploration | π₯οΈ slides 20 β¨οΈ ae 15 β ae 15 | AEs 13-15 due 6/16 by 11:59 PM |
Β | Lab 5: Modeling II | Β | π» lab 5 β lab 5 | lab 5 due 6/16 by 11:59 PM |
Mon, June 17 | Lec: Making decisions with randomization tests and exam review | π ims - chp 11 | π₯οΈ slides 21 β¨οΈ ae 16 β ae 16 | Β |
Β | Lab: Exam 2 review | Β | π exam 2 review β exam 2 review | Β |
Tu, June 18 | Lec: Communicating data science results effectively | π₯ Tips for effective data visualization π ims - chp 6 π r4ds - chp 10 π₯ Doing data science | π₯οΈ slides 23 β¨οΈ ae 17 β ae 17 β¨οΈ 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 | π₯οΈ slides 24 β¨οΈ 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 | π 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 | π 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 |