Welcome Back!
PSY 504: Advanced Statistics
Princeton University
Janurary 29, 2024
Course content
I will only use Canvas to:
- Send announcements
All course content located here:
PSY 504: Advanced Statistics
PSY 504: Advanced Statistics
Multilevel modeling
Missing data
Generalized linear models
Beta regression
Bayesian data analysis
Mediation
Path analysis (SEM)
Factor analysis
In this class you will:
Read some stuff
Apply some stuff
Write some stuff
Student learning outcomes
Make informed analytic decisions
Run and code analyses in R
Interpret output and summarize results of the analyses
Effectively communicate results from statistical analyses to a general audience
Use Quarto to write reproducible reports and GitHub for version control and collaboration
Assignments
Mini-lecture
Labs
Tutorial blog post
Grades
No points/percentages associated with assignments
Default grade is A
In order to keep A you MUST COMPLETE ALL ASSIGNMENTS
You can earn A+ if you turn exemplary work
A- and below, If you turn in substandard work (missing labs, late labs, half finished labs)
Important
This marking scheme is purposefully non-quantitative so that you will focus on learning instead of on your marks
Assignments
Readings
Each week you will read a variety of articles and textbook chapters
Before class
After class (materials to help with labs)
Mini-lectures/discussion
~15 minutes
High level overview of the topic
A brief introduction
Important concepts
limitations/advantages
Relevance to psychology
Examples and applications
- Walk us through an example from your own work or something of interest to you
A few questions for the class
Labs
Every week (Wednesday) we will have a lab activity covering material from that week
Lab should be completed in QMD and rendered as HTML document (needs to be reproducible!)
- Have until Sunday at midnight to turn them in
I will provide feedback and comments that you should incorporate into a revision
Note
I will not accept labs more than a week late!
Tutorial/blog post
The final project will require you to use one of the methods discussed in class to analyze data (your own or publicly available data) and write a short blog post walking us through the process (i.e., pre-processing, analysis, and interpretation of results)
Note
- Will go over how to create Quarto blog/website on Wednesday
Attendance
Come to class
- Come on time!
If you are sick, please stay home
- Can start a Zoom session
Office hours
M 1:00 P.M.- 3:00 P.M.; W 1:00 P.M. - 2:00 P.M. 🪑
By appointment
- Calendly: https://calendly.com/jg9120/30min
Recommended text
McCoach, D. B., & Cintron, D. (2022). Introduction to Modern Modelling Methods (1st edition). SAGE Publications Ltd.
Recommended text
Xing Liu (2023). Categorical Data Analysis and Multilevel Modeling Using R (1st edition). SAGE Publications Ltd.
Software
R
RStudio (IDE)
Quarto (QMD)
Note
If you need help installing these please ask me. Instructions can be found here: https://psy504-s24-advstats.netlify.app/schedule/01-week
Class Format
Lectures (Monday)
Peers will introduce you to the basics of each topic and get you started with examples
I’ll highlight main concepts/walk through example(s)
How to run analysis in R
Interpretation
Write-up
Lab (Wednesday)
Wednesday will be reserved for application-based activities (labs)
- Also a time to seek clarification on topics from me or your classmates
- Can work in groups (strongly encouraged!)
Precept time
PSY 505
- Tuesdays 11:00 A.M. - 1:00 P.M.
Speaker and workshop focused (great list of speakers this semester)
No HW or papers
Class questions
- Any general questions about course content or assignments should be posted on the class GitHub Issues. There is a chance another student has already asked a similar question, so please check the other posts before adding a new question. If you know the answer to a question posted in the discussion forum, I encourage you to respond!
Schedule
Survey
Go here
Rank order preference
Will try to give your #1 choice
- At least top 3 😊