Day 7 — Wednesday, January 18th, 2023
Wednesday January 18th
- 1:30-2:00 Lecture: A Data Analysis from Start to Finish
- 2:00-2:30 Lecture: Longitudinal Data Analysis
- 2:30-3:00 Lecture: Best practices for reporting on missing data
- 3:00-3:30 Lecture: Intro to accessible exploratory data analysis methods: Correlation, principal components analysis, variable importance
- 3:30-3:40 Break
- 3:40-4:00 Discussion: What are the ethical principles involved in data analysis? What are the risks involved?
- 4:00-4:30 Lecture: Clean Code and Considerate Coding
- 4:30-5:30 Free time to work together on the final project, chat with classmates, peruse recommended materials
Homework:
- Peer Review Homework 5
Recommended Materials:
- Harms and Ethics in Data Science and Machine Learning:
- The Data Science Ethics chapter from the Modern Data Science with R book: https://mdsr-book.github.io/mdsr2e/ch-ethics.html
Video Recording
Resources
Lecture 2: Exploratory data analysis – Longitudinal data analysis
link to longitudinal_eda.R script
link to make_simulated_data.R script
Lecture 3: Missing data
link to view slides fullscreen
link to slide PDFs
link to missing-demo.R script