STA 199: Introduction to Data Science

Section 2 - Dr. Elijah Meyer

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 dow date what topic prepare slides ae_sa hw hw_sa lab lab_sa exam project notes
1 W 11 January NA No Class
F 13 January Lec-1 Welcome to STA 199
2 Tu 17 January Lab-0 Hello R! Release Lab 0: https://github.com/ElijahMeyer3/lab-0-public
W 18 January Lec-2 Meet the toolkit
F 20 January Lec-3 Visualizing various types of data Lab 0 Due
3 Tu 24 January Lab-1 Data visualization Release Lab 1 / Release HW 1
W 25 January Lec-4 Grammar of data wrangling
F 27 January Lec-5 Grammar of data wrangling + Data types intro Lab 1 Due
4 Tu 31 January Lab-2 Data Wrangling HW 1 Due / Release Lab 2
W 1 February Lec-6 Working with multiple data frames Exam Review Release: https://sakai.duke.edu/access/content/group/3c0a7e6f-cbfc-4e54-bcbf-faf6fa16761c/practice1.pdf
F 3 February Lec-7 Tidying data
5 Tu 7 February Lab-3 Data tidying Lab 2 Due / Release Lab 3
W 8 February Lec-8 Debugging + ggplot practice
F 10 February Lec-9 Exam Review Lab 3 Due (5:00 PM) / Exam Released (5:00PM - 6:00PM)
6 Tu No Lab: Work on Exam 1 Exam 1 Due
W 15 February Lec-10 Introduction to probability
F 17 February Lec-11 More Probability Release HW 2
7 Tu 21 February Lab-4 Merge Conflicts
W 22 February Lec-12 Simple regression
F 24 February Lec-13 Multiple regression I HW 2 Due
8 Tu 28 February Lab-5 Predicting a numerical outcome
W 1 March Lec-14 Multiple regression II Release Project Instructions; Release HW 3
F 3 March Lec-15 Model selection
9 Tu 7 March Lab-6 Work on project proposal
W 8 March Lec-16 Logistic Regression Release HW 6
F 10 March Lec-17 Prediction Project Proposal Due; HW3 Due; Release Project Draft Report Instructions
10 Tu 14 March No class -- Spring Break
W 15 March No class -- Spring Break
F 17 March No class -- Spring Break
11 Tu 21 March Logistic Regression Lab
W 22 March Lec 18 Bootstrap HW4 Release
F 24 March Lec 19 Bootstrap + Central limit theorem I
12 Tu 28 March Work on project proposal
W 29 March Confidence Intervals + Central limit theorem II
F 31 March Hypothesis testing I HW4 Due
13 Tu 4 April Hypothesis testing Lab
W 5 April Hypothesis testing II Release HW 5
F 7 April Hypothesis testing III Project Draft Report Due (5:00 PM)
14 Tu 11 April Project peer review
W 12 April Hypothesis testing wrap up
Th 13 April HW 5 Due
F 14 April Exam 2 Review Project Peer Evaluations Due; Release Exam 2
15 Tu 18 April No lab: exam 2 Exam 2 Due
W 19 April Communicating Visualizations Effectively
Th 20 April
F 21 April Communicating Visualizations Effectively + Spatial Data Visualization
16 Tu 25 April Project presentations
W 26 April (Optional) R-Shiny Interactive Plots
F 28 April Final Project Due; Statistics Experience HW 6 Due