STA 199: Introduction to Data Science & Statistical Thinking
This page contains an outline of the topics, content, and assignments for the semester! Entries for future dates are tentative; the timeline of topics, assignments, and due dates might be changed throughout the session at the instructorβs discretion. All material changes will be communicated with the students in a timely manner.
| WEEK | DATE | TOPIC | MATERIALS | DUE | PREPARE |
|---|---|---|---|---|---|
| 1 | Mon, Jun 29 | Welcome | π₯οΈ slides 00 β¨οΈ ae 00 |
GitHub username - End of Lecture | |
| Mon, Jun 29 | Lab 0 | π» lab 0 | Lab 0 - End of Lab | ||
| Tue, Jun 30 | Meet the Toolkit | π₯οΈ slides 01 ποΈ notes 01 β¨οΈ ae 01 |
π r4ds - intro π ims - chp 1 π₯ Meet the toolkit :: R and RStudio π₯ Meet the toolkit :: Quarto |
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| Wed, Jul 1 | Grammar of Data Visualization | π₯οΈ slides 02 ποΈ notes 02 β¨οΈ ae 02 β ae 02 |
Drop/Add Deadline 11:59pm | π r4ds - chp 1 π ims - chp 4 |
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| Thu, Jul 2 | Grammar of Data Transformation | π₯οΈ slides 03 ποΈ notes 03 β¨οΈ ae 03 β ae 03 |
π r4ds - chp 2 π r4ds - chp 3.1-3.5 π₯ Grammar of data transformation π₯ Code along :: Flights and pipes |
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| Thu, Jul 2 | Lab 1 | π» lab 1 | π r4ds - chp 2 π ims - chp 5 |
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| Fri, Jul 3 | NO CLASS - Independence Day | ||||
| 2 | Mon, Jul 6 | Exploratory Data Analysis I | π₯οΈ slides 04 ποΈ notes 04 β¨οΈ ae 04 β ae 04 |
π r4ds - chp 3.6-3.7 π₯ Visualizing and summarizing categorical data π₯ Visualizing and summarizing numerical data π₯ Visualizing and summarizing relationships π₯ Code along :: Star Wars characters |
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| Tue, Jul 7 | Exploratory Data Analysis II | π₯οΈ slides 05 ποΈ notes 05 β¨οΈ ae 05 β ae 05 |
π ims - chp 5 π ims - chp 6 π₯ Code along :: Diving deeper with Palmer Penguins |
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| Wed, Jul 8 | Tidying Data | π₯οΈ slides 06 ποΈ notes 06 β¨οΈ ae 06 β ae 06 |
Lab 1 - 11:59PM ET | π r4ds - chp 5 π ims - chp 6 |
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| Thu, Jul 9 | Joining Data | π₯οΈ slides 07 ποΈ notes 07 β¨οΈ ae 07 β ae 07 |
π₯ Joining data π₯ Code along :: Continent populations π r4ds - chp 19.1-19.3 |
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| Thu, Jul 9 | Lab 2 | π» lab 2 | π r4ds - chp 4 π₯ Tidy data π₯ Tidying data π₯ Code Along: Population over time |
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| Fri, Jul 10 | Data Types and Classes | π₯οΈ slides 08 ποΈ notes 08 β¨οΈ ae 08 β ae 08 |
π₯ Data types π₯ Data classes π₯ Code along :: Thatβs my type π r4ds - chp 16 |
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| Sun, Jul 12 | |||||
| 3 | Mon, Jul 13 | Importing and Recoding Data | π₯οΈ slides 09 ποΈ notes 09 β¨οΈ ae 09 β ae 09 |
Lab 2 - 11:59PM ET | π₯ Importing data π₯ Code along :: Halving CO2 emissions π₯ Code along :: Student survey π r4ds - chp 7 π r4ds - chp 17.1 - 17.3 |
| Mon, Jul 13 | Lab 3 | π» lab 3 | |||
| Tue, Jul 14 | Communication via Data Science | π₯οΈ slides 10 ποΈ notes 10 β¨οΈ ae 10 β ae 10 |
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| Wed, Jul 15 | Data Ethics + Midterm Review | π₯οΈ slides 11 ποΈ notes 11 β¨οΈ ae 11 β ae 11 |
π mdsr - chp 8 π How to make a racist AI in R without really trying π₯ Alberto Cairo - How charts lie π₯ Joy Buolamwini - How Iβm fighting bias in algorithms |
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| Thu, Jul 16 | Midterm (lecture + lab sessions) | ||||
| Fri, Jul 17 | Project Milestone 1 - Collaboration | πmilestone 1 |
Project Milestone 1 - 11:00AM ET | ||
| Sun, Jul 19 | Lab 3 - 11:59PM ET | ||||
| 4 | Mon, Jul 20 | The Language of Models | π₯οΈ slides 12 ποΈ notes 12 β¨οΈ ae 12 β ae 12 |
π₯ The language of models π ims - chp 7.1 π₯ Fitting and interpreting models π₯ Modeling nonlinear relationships |
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| Mon, Jul 20 | Project Milestone 2 - Proposals | πmilestone 2 |
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| Tue, Jul 21 | Simple Linear Regression | π₯οΈ slides 13 ποΈ notes 13 β¨οΈ ae 13 β ae 13 |
π₯ Linear regression with a categorical predictor π₯ Outliers in linear regression π₯ Code along :: Modeling fish π ims - chp 7.2 |
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| Wed, Jul 22 | Multiple Linear Regression I | π₯οΈ slides 14 ποΈ notes 14 |
Project Milestone 2 - 11:59PM ET | π₯ Linear regression with multiple predictors π₯ Main and interaction effects π ims - chp 8.1-8.2 π ims - chp 8.3-8.5 |
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| Thu, Jul 23 | Multiple Linear Regression II | π₯οΈ slides 15 ποΈ notes 15 β¨οΈ ae 14 β ae 14 |
π₯ Code along :: Modeling interest rates | ||
| Thu, Jul 23 | Lab 4 | π» lab 4 | |||
| Fri, Jul 24 | Linear Regression Diagnostics | π₯οΈ slides 16 ποΈ notes 16 |
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| Sun, Jul 26 | Lab 4 - 11:59PM ET |
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| 5 | Mon, Jul 27 | Logistic Regression I | π₯οΈ slides 17 ποΈ notes 17 β¨οΈ ae 15 β ae 15 |
π₯ Logistic regression π₯ Code along :: Building a spam filter π ims - chp 9 |
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| Mon, Jul 27 | Lab 5 | π» lab 5 | |||
| Tue, Jul 28 | Logistic Regression II / Modeling Wrap-Up | π₯οΈ slides 18 ποΈ notes 18 β¨οΈ ae 16 β ae 16 |
π₯ Clasification and decision errors π₯ Overfitting and spending your data |
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| Wed, Jul 29 | Interval Estimation | π₯οΈ slides 19 ποΈ notes 19 β¨οΈ ae 17 β ae 17 |
Project Milestone 3 - 11:59PM ET | π₯ Quantifying uncertainty π₯ Bootstrapping π₯ Code along :: Bootstrapping Duke Forest houses π ims - chp 11 π ims - chp 12 |
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| Thu, Jul 30 | Hypothesis Testing | π₯οΈ slides 20 ποΈ notes 20 β¨οΈ ae 18 β ae 18 |
π₯ Hypothesis testing π ims - chp 11 |
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| Thu, Jul 30 | Project Milestone 4 - Peer Review | πmilestone 4 |
Project Milestone 4 - 12:30PM ET |
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| Fri, Jul 31 | More Inference | π₯οΈ slides 21 ποΈ notes 21 β¨οΈ ae 19 β ae 19 |
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| Sun, Aug 2 | Lab 5 - 11:59PM ET |
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| 6 | Mon, Aug 3 | Causality from Randomized Experiments | π₯οΈ slides 22 ποΈ notes 22 β¨οΈ ae 20 β ae 20 |
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| Mon, Aug 3 | Lab 6 | π» lab 6 | |||
| Tue, Aug 4 | Causality from Observational Studies | π₯οΈ slides 23 ποΈ notes 23 |
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| Wed, Aug 5 | Project Workday | ||||
| Thu, Aug 6 | Project Milestone 5 - Presentations | πmilestone 5 |
Project - 9:30 AM | ||
| Fri, Aug 7 | Review | π₯οΈ slides 24 ποΈ notes 24 π€ͺ Kahoot! |
Lab 6 - 11:59pm ET | ||
| Sun, Aug 9 | FINAL EXAM (9am - 12pm) |