STA 199: Introduction to Data Science and Statistical Thinking

This page contains an outline of the topics, content, and assignments for the semester. Note that this schedule will be updated as the semester progresses and the timeline of topics and assignments might be updated throughout the semester.

WEEK DATE PREPARE TOPIC MATERIALS DUE
1 Wed, Jan 10

Lab 0: Hello, World and STA 199!

πŸ’» lab 0

Thu, Jan 11

Welcome to STA 199

πŸ–₯️ slides 00
⌨️ ae 00
2 Mon, Jan 15

No lab - Martin Luther King Jr. Day holiday


Tue, Jan 16

πŸ“— r4ds - intro
πŸ“˜ ims - chp 1

Meet the toolkit

πŸ–₯️ slides 01
⌨️ ae 01

Thu, Jan 18

πŸ“— r4ds - chp 1
πŸŽ₯ Data and visualization
πŸŽ₯ Visualising data with ggplot2

Grammar of graphics

πŸ–₯️ slides 02
⌨️ ae 02
3 Mon, Jan 22

πŸ“— r4ds - chp 2

Lab 1: Data visualization

πŸ’» lab 1

Tue, Jan 23

πŸ“˜ ims - chp 4
πŸ“˜ ims - chp 5
πŸŽ₯ Visualizing numerical data
πŸŽ₯ Visualizing categorical data

Visualizing various types of data

πŸ–₯️ slides 03
⌨️ ae 02 (cont.)

Thu, Jan 25

πŸ“˜ ims - chp 6

Data visualization overview

πŸ–₯️ slides 04
⌨️ ae 03
4 Mon, Jan 29

πŸŽ₯ Grammar of data wrangling
πŸ“— r4ds - chp 3.1-3.5

Lab 2: Data wrangling

πŸ’» lab 2

Lab 1 at 8 am

Tue, Jan 30

πŸŽ₯ Working with a single data frame
πŸ“— r4ds - chp 3.6-3.7
πŸ“— r4ds - chp 4

Grammar of data wrangling

πŸ–₯️ slides 05
⌨️ ae 04

Thu, Feb 1

πŸŽ₯ Tidying data
πŸ“— r4ds - chp 5

Tidying data

πŸ–₯️ slides 06
⌨️ ae 05
5 Mon, Feb 5

πŸŽ₯ Working with multiple data frames

Lab 3: Data tidying and joining

πŸ’» lab 3

Lab 2 at 8 am

Tue, Feb 6

πŸ“— r4ds - chp 19.1-19.3

Working with multiple data frames


Thu, Feb 8

πŸŽ₯ Data types
πŸŽ₯ Data classes
πŸ“— r4ds - chp 16

Data types and classes

6 Mon, Feb 12

Work on Exam 1 Review

Lab 3 at 8 am

Tue, Feb 13

Importing and recoding data


Thu, Feb 15

Exam 1 - In-class + take-home released

7 Mon, Feb 19

Project milestone 1 - Working collaboratively

Exam 1 take-home at 8 am

Tue, Feb 20

Web scraping


Thu, Feb 22

Functions + iteration

8 Mon, Feb 26

Lab 4: Topic TBA

πŸ’» lab 4

Project milestone 1 at 8 am

Tue, Feb 27

Data science ethics - Misrepresentation


Thu, Feb 29

Data science ethics - Algorithmic bias + data privacy

9 Mon, Mar 4

Lab 5: Topic TBA

πŸ’» lab 5

Lab 4 at 8 am

Tue, Mar 5

The language of models


Thu, Mar 7

Linear regression with a single predictor

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

Lab 5 at 8 am

Tue, Mar 19

Linear regression with multiple predictors


Thu, Mar 21

Overfitting and other concerns

12 Mon, Mar 25

Lab 6: Topic TBA

πŸ’» lab 6

Project milestone 2 at 8 am

Tue, Mar 26

Logistic regression


Thu, Mar 28

Modeling overview

13 Mon, Apr 1

Lab 7: Topic TBA

πŸ’» lab 7

Lab 6 at 8 am

Tue, Apr 2

Quantifying uncertainty with bootstrap intervals


Thu, Apr 4

Making decisions with randomization tests

14 Mon, Apr 8

Work on Exam 2 Review

Lab 7 at 8 am

Tue, Apr 9

Inference overview


Thu, Apr 11

Exam 2 - In-class + take-home released

15 Mon, Apr 15

Project milestone 3 - Peer review

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

Tue, Apr 16

Communicating data science results effectively


Thu, Apr 18

Customizing Quarto reports and presentations

16 Mon, Apr 22

Project milestone 4 - Project presentations

Project presentations + writeup at the beginning of lab session

Tue, Apr 23

Looking further: Topic TBA