WEEK |
DATE |
PREPARE |
TOPIC |
MATERIALS |
DUE |
|---|---|---|---|---|---|
| 1 | Wed, Jan 10 | Lab 0: Hello, World and STA 199! |
π» lab 0 |
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| Thu, Jan 11 | Welcome to STA 199 |
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| 2 | Mon, Jan 15 | No lab - Martin Luther King Jr. Day holiday |
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| Tue, Jan 16 | π r4ds - intro |
Meet the toolkit |
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| Thu, Jan 18 | π r4ds - chp 1 |
Grammar of graphics |
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| 3 | Mon, Jan 22 | π r4ds - chp 2 |
Lab 1: Data visualization |
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| Tue, Jan 23 | π ims - chp 4 |
Visualizing various types of data |
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| Thu, Jan 25 | π ims - chp 6 |
Data visualization overview |
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| 4 | Mon, Jan 29 | π₯ Grammar of data wrangling |
Lab 2: Data wrangling |
Lab 1 at 8 am |
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| Tue, Jan 30 | π₯ Working with a single data frame |
Grammar of data wrangling |
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| Thu, Feb 1 | π₯ Tidying data |
Tidying data |
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| 5 | Mon, Feb 5 | Lab 3: Data tidying and joining |
Lab 2 at 8 am |
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| Tue, Feb 6 | π r4ds - chp 19.1-19.3 |
Joining data |
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| Thu, Feb 8 | π₯ Data types |
Data types and classes |
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| 6 | Mon, Feb 12 | Work on Exam 1 Review |
π exam 1 review |
Lab 3 at 8 am |
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| Tue, Feb 13 | Exam 1 Review |
π₯οΈ slides 09 |
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| Thu, Feb 15 | Exam 1 - In-class + take-home released |
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| 7 | Mon, Feb 19 | Project milestone 1 - Working collaboratively |
π project milestone 1 |
Exam 1 take-home at 8 am |
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| Tue, Feb 20 | π₯ Importing data |
Importing and recoding data |
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| Thu, Feb 22 | π₯ Web scraping |
Web scraping |
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| 8 | Mon, Feb 26 | Lab 4: Web scraping and ethics |
Project milestone 1 at 8 am |
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| Tue, Feb 27 | π₯ Functions |
Working with Chat GPT |
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| Thu, Feb 29 | π₯ Misrepresentation |
Data science ethics |
π₯οΈ slides 13 |
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| 9 | Mon, Mar 4 | Lab 5: Topic TBA |
Lab 4 at 8 am |
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| Tue, Mar 5 | π₯ The language of models |
The language of models |
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| Thu, Mar 7 | π₯ Fitting and interpreting models |
Linear regression with a single predictor |
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| 10 | Mon, Mar 11 | π΄ No lab - Spring Break |
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| Tue, Mar 12 | π΄ No lecture - Spring Break |
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| Thu, Mar 14 | π΄ No lecture - Spring Break |
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| 11 | Mon, Mar 18 | Project milestone 2 - Project proposals |
π project milestone 2 |
Lab 5 at 8 am |
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| Tue, Mar 19 | π₯ Models with multiple predictors |
Linear regression with multiple predictors I |
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| Thu, Mar 21 | π ims - chp 8.3-8.5 |
Linear regression with multiple predictors II |
π₯οΈ slides 17 |
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| 12 | Mon, Mar 25 | Lab 6: Modeling I |
Project milestone 2 at 8 am |
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| Tue, Mar 26 | Model selection and overfitting |
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| Thu, Mar 28 | π ims - chp 9 |
Logistic regression |
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| 13 | Mon, Apr 1 | Lab 7: Modeling II |
Lab 6 at 8 am |
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| Tue, Apr 2 | π₯ Quantifying uncertainty |
Quantifying uncertainty with bootstrap intervals |
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| Thu, Apr 4 | π ims - chp 11 |
Making decisions with randomization tests |
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| 14 | Mon, Apr 8 | Work on Exam 2 Review |
π exam 2 review |
Lab 7 at 8 am |
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| Tue, Apr 9 | Exam 2 Review |
π₯οΈ slides 22 |
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| Thu, Apr 11 | Exam 2 - In-class + take-home released |
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| 15 | Mon, Apr 15 | Project milestone 3 - Peer review |
π project milestone 3 |
Exam 2 take-home at 8 am |
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| Tue, Apr 16 | π₯ Tips for effective data visualization |
Communicating data science results effectively |
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| Thu, Apr 18 | π₯ Doing data science |
Customizing Quarto reports and presentations |
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| 16 | Mon, Apr 22 | Project milestone 4 - Project presentations |
π project milestone 4 |
Project presentations at the beginning of lab session |
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| Tue, Apr 23 | Looking further: Interactive web applications with Shiny |
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| Wed, Apr 24 | Project writeup at 8 am |
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.