1 Wed, Jan 10

Lab 0: Hello, World and STA 199!

💻 lab 0

Thu, Jan 11

Welcome to STA 199

🖥️ slides 00
⌨️ ae 00

2 Mon, Jan 15

No lab - Martin Luther King Jr. Day holiday

Tue, Jan 16

📗 r4ds - intro
📘 ims - chp 1

Meet the toolkit

🖥️ slides 01
⌨️ ae 01

Thu, Jan 18

📗 r4ds - chp 1
🎥 Data and visualization
🎥 Visualising data with ggplot2

Grammar of graphics

🖥️ slides 02
⌨️ ae 02
✅ ae 02

3 Mon, Jan 22

📗 r4ds - chp 2

Lab 1: Data visualization

💻 lab 1
✅ lab 1

Tue, Jan 23

📘 ims - chp 4
📘 ims - chp 5
🎥 Visualizing numerical data
🎥 Visualizing categorical data

Visualizing various types of data

🖥️ slides 03
⌨️ ae 02 (cont.)
✅ ae 02

Thu, Jan 25

📘 ims - chp 6

Data visualization overview

🖥️ slides 04
⌨️ ae 03
✅ ae 03

4 Mon, Jan 29

🎥 Grammar of data wrangling
📗 r4ds - chp 3.1-3.5

Lab 2: Data wrangling

💻 lab 2
✅ lab 2

Lab 1 at 8 am

Tue, Jan 30

🎥 Working with a single data frame
📗 r4ds - chp 3.6-3.7
📗 r4ds - chp 4

Grammar of data wrangling

🖥️ slides 05
⌨️ ae 04
✅ ae 04

Thu, Feb 1

🎥 Tidying data
📗 r4ds - chp 5

Tidying data

🖥️ slides 06
⌨️ ae 05
✅ ae 05

5 Mon, Feb 5

🎥 Working with multiple data frames

Lab 3: Data tidying and joining

💻 lab 3
✅ lab 3

Lab 2 at 8 am

Tue, Feb 6

📗 r4ds - chp 19.1-19.3

Joining data

🖥️ slides 07
⌨️ ae 06
✅ ae 06

Thu, Feb 8

🎥 Data types
🎥 Data classes
📗 r4ds - chp 16

Data types and classes

🖥️ slides 08
⌨️ ae 07
✅ ae 07

6 Mon, Feb 12

Work on Exam 1 Review

📝 exam 1 review
✅ exam 1 review

Lab 3 at 8 am

Tue, Feb 13

Exam 1 Review

🖥️ slides 09

Thu, Feb 15

Exam 1 - In-class + take-home released

7 Mon, Feb 19

Project milestone 1 - Working collaboratively

📓 project milestone 1

Exam 1 take-home at 8 am

Tue, Feb 20

🎥 Importing data
🎥 Recoding data
📗 r4ds - chp 7
📗 r4ds - chp 17.1 - 17.3

Importing and recoding data

🖥️ slides 10
⌨️ ae 08
✅ ae 08

Thu, Feb 22

🎥 Web scraping
🎥 Scraping top 250 movies on IMDB
🎥 Web scraping considerations
📗 r4ds - chp 24.1 - 24.6

Web scraping

🖥️ slides 11
⌨️ ae 09
⌨️ ae 09
✅ ae 09

8 Mon, Feb 26

Lab 4: Web scraping and ethics

💻 lab 4
✅ lab 4

Project milestone 1 at 8 am

Tue, Feb 27

🎥 Functions
🎥 Iteration
📗 r4ds - chp 25.1 - 25.2

Working with Chat GPT

🖥️ slides 12
⌨️ ae 09
✅ ae 09

Thu, Feb 29

🎥 Misrepresentation
🎥 Data privacy
🎥 Algorithmic bias
📕 mdsr - chp 8
🎥 Alberto Cairo - How charts lie
🎥 Joy Buolamwini - How I’m fighting bias in algorithms

Data science ethics

🖥️ slides 13

9 Mon, Mar 4

Lab 5: Topic TBA

💻 lab 5
✅ lab 5

Lab 4 at 8 am

Tue, Mar 5

🎥 The language of models
📘 ims - chp 7.1

The language of models

🖥️ slides 14
⌨️ ae 10
✅ ae 10

Thu, Mar 7

🎥 Fitting and interpreting models
🎥 Modeling nonlinear relationships
📘 ims - chp 7.2

Linear regression with a single predictor

🖥️ slides 15
⌨️ ae 11
✅ ae 11

10 Mon, Mar 11

🌴 No lab - Spring Break

Tue, Mar 12

🌴 No lecture - Spring Break

Thu, Mar 14

🌴 No lecture - Spring Break

11 Mon, Mar 18

Project milestone 2 - Project proposals

📓 project milestone 2

Lab 5 at 8 am

Tue, Mar 19

🎥 Models with multiple predictors
🎥 More models with multiple predictors
📘 ims - chp 8.1-8.2

Linear regression with multiple predictors I

🖥️ slides 16
⌨️ ae 12
✅ ae 12

Thu, Mar 21

📘 ims - chp 8.3-8.5

Linear regression with multiple predictors II

🖥️ slides 17

12 Mon, Mar 25

Lab 6: Modeling I

💻 lab 6
✅ lab 6

Project milestone 2 at 8 am

Tue, Mar 26

🎥 Logistic regression
🎥 Prediction and overfitting

Model selection and overfitting

🖥️ slides 18
⌨️ ae 13
✅ ae 13

Thu, Mar 28

📘 ims - chp 9

Logistic regression

🖥️ slides 19
⌨️ ae 14
✅ ae 14

13 Mon, Apr 1

Lab 7: Modeling II

💻 lab 7
✅ lab 7

Lab 6 at 8 am

Tue, Apr 2

🎥 Quantifying uncertainty
🎥 Bootstrapping
📘 ims - chp 12

Quantifying uncertainty with bootstrap intervals

🖥️ slides 20
⌨️ ae 15
✅ ae 15

Thu, Apr 4

📘 ims - chp 11

Making decisions with randomization tests

🖥️ slides 21
⌨️ ae 16
✅ ae 16

14 Mon, Apr 8

Work on Exam 2 Review

📝 exam 2 review
✅ exam 2 review

Lab 7 at 8 am

Tue, Apr 9

Exam 2 Review

🖥️ slides 22

Thu, Apr 11

Exam 2 - In-class + take-home released

15 Mon, Apr 15

Project milestone 3 - Peer review

📓 project milestone 3

Exam 2 take-home at 8 am
Project milestone 3 at the end of lab session

Tue, Apr 16

🎥 Tips for effective data visualization
📘 ims - chp 6
📗 r4ds - chp 10

Communicating data science results effectively

🖥️ slides 23
⌨️ ae 17
✅ ae 17

Thu, Apr 18

🎥 Doing data science

Customizing Quarto reports and presentations

🖥️ slides 24
⌨️ ae 18

16 Mon, Apr 22

Project milestone 4 - Project presentations

📓 project milestone 4

Project presentations at the beginning of lab session

Tue, Apr 23

Looking further: Interactive web applications with Shiny

🖥️ slides 25
⌨️ ae 19

Wed, Apr 24

Project writeup at 8 am