Overview
Week 1
Get your feet wet
- Why psychologists program
- The anatomy of code and code editors
Week 2
Be the boss of columns
- Data types
- Logical and relational operators
- Tidy dataframe manipulation
- Troubleshooting as an experimentation skill
Due: Problem set 1
Week 3
Dirty data done dirt cheap
- Joining data
- Reshaping data
- Dealing with irregular data
Due: Problem set 2
Week 4
Writing code
- R scripts and R Markdown
- Scripting hygiene
- Debugging in the code editor
Due: Problem set 3
Week 5
Big data: the good, the bad, the ugly
- Reading and writing data into and out of R
- Working with behavioral data from the internet
- The pros and cons of “big data”
Due: Problem set 4
Week 6
An eye on data visualization
- The grammar of graphics
- Graphs as communication devices
Due: Problem set 5
Midterm take-home exam open this week
Week 7
The medium is the (scientific) message
- Graph customization
- Visual communication best practices
Due: Midterm exam
Week 8
Putting the stats in statistical computing
- Working with regression models
Due: Problem set 6
Week 9
Putting more stats in statistical computing
- Simulating data
- Power analysis
Due: Problem set 7
Week 10
Capital-P Programming
- Nested data and other list columns
- Writing functions
- Advanced debugging
Due: Problem set 8
Week 11
Reproducibility: what is it good for?
- Preparing and documenting code and data for sharing
- Code testing
Due: Problem set 9
Week 12
Stop, collaborate, and listen
- Version control with git
- Peer reviewing code effectively and respectfully
Due: Problem set 10
Week 13
Give them the old razzle dazzle
- Formatting and publishing analysis write-ups
- Creating interactive plots and tables
Due: Problem set 11
Final take-home exam open this week
Week 14
People’s choice
- Student-selected topics
Due: Final exam