QuACK
Quantitative analysis and coding knowledge (UC Berkeley, Psychology)
Quantitative Analysis and Coding Knowledge (QuACK) course page
Welcome to QuACK 2022!
This semester-long course is for PhD students by PhD students. We will focus on teaching fudemental programming skills in R to prepare you for research and data anlysis. The workshop also helps prepare first-year PhD students for Psych 205: Data analysis.
The class takes a hands-on workshop style format focusing on using real data!
To take the class for credit: Register through CalCentral:
- Course Number: 14178
- Select 2 credits (since it is 2 hours a week)
- Select to take the class Pass/No Pass
See the FAQs below for more info
Instructors
The course is developed and taught by Elena Leib and Willa Voorhies, who are 5th year PhD students in the department.
Core Goals
1) Provide hands-on training in fundamental programming and data skills with real data.
2) Build an inclusive, supportive and positive space for learning and teaching quantitative skills.
Schedule
We will meet weekly on Tuesdays from 5pm - 7pm PST in BWW 1211. First session August 30th!
Each session will start with a live demo focusing on fundemental data skills. We will then work independently and in groups to apply these skills to real data. Finally, we will finish each session with a group discussion centering around challenges you faced working with the data and ways to address and overcome these challenges.
As you will see, the sessions build on each other. If you miss a session, we encourage you to watch the recording and try the practice problems on your own.
| Week | Topic | practice materials | live demo script & answer key | slides | recording | ||
|---|---|---|---|---|---|---|---|
| Week 1 (8/30) | Intro to R & Programming | w1_materials | w1_key | w1_slides | w1_recording | ||
| Week 2 (9/6) | Working directories and reading in data | w2_materials | w2_key | w2_slides | w2_recording | ||
| Week 3 (9/13) | Intro to the tidyverse and data wrangling - Part 1 | w3_materials | w3_key | w3_slides | w3_recording | ||
| Week 4 (9/20) | Data wrangling - Part 2 | w4_materials | w4_key | no slides | w4_recording | ||
| Week 5 (9/27) | Intro to data visualization (ggplot) - Part 1 | w5_materials | w5_key | w5_slides | w5_recording | ||
| Week 6 (10/4) | Data visualization - Part 2 | w6_materials | w6_key | no slides | w6_recording | ||
| Week 7 (10/11) | Intro to loops | w7_materials | w7_key | w7_slides | w7_recording | ||
| Week 8 (10/18) | Loops continued and random sampling | week8_materials | w8_key | no slides | see last year w8_recording | ||
| Week 9 (10/25) | Class Cancelled | ||||||
| Week 10 (11/1) | Random Sampling pt 2 | w10_materials | w10_key | no slides | w10_recording | ||
| Week 11 (11/8) | Functions! | w11_materials | w11_key | w11_slides | w11_recording | ||
| Week 12 (11/15) | Discussion/Flex week: | No class due to strike | |||||
| Week 13 (11/22) | Thanksgiving Week: | No class | |||||
| Week 14 (11/29) | Putting it all together | No class due to strike | |||||
| Week 15 (12/6) | Celebration! | postponed until spring |
Materials guide
We are committed to open science and we make all of our resources and teaching materials freely available for offline learning.
Each week we will be posting the following materials:
- Practice materials: Please download the practice material before each session. This will include any starter code and prompts for the independent and/or group work. The best way to learn to program is to practice! So if you are participating asynchronously or if you miss a session, we encourage you to try the practice work on your own and use the slack channel to share any comments or ask questions you might have!
- Live demo script: Each session will begin with a demo where we introduce some fundemental skills and key concepts that will help you with the practice materials. We will post these after each session. This will also include answer keys for the group activity if applicable.
- Slides: Any slides used will be made available for download after the session.
- Recording: We will be recording all of our sessions. If you miss a session we encourage you to watch the recording!
FAQs
I can’t attend all of the sessions. Should I still enroll?
You will not be penalzied for missing sessions. However, we do encourage everyone to attend as many sessions as possible as the sessions build on eachother. It is also a great opportunity to get to know your cohort better!
How much experience with programming, R, or statistics is expected?
No experience is expected or required! We are going to build up the foundational skills you need to work with data in R. If you do have some past experience with R, this workshop will give you the chance to brush up on your skills and learn to apply them to real data. The goal is to give you the tools (and confidence!) to continue learning in your lab, on your own, and/or through other online tools. We will also share additional resources so you can keep learning R on your own.
We will not be teaching statistics in this workshop. However, this course will set you up nicely for a statistics course by giving you hands-on experience working with real data in R and the fundemental programming skills that are required for statistical analyses.
What is the time commitment for this course?
This is a semester-long workshop that meets once a week for 2 hours. There are no required assignments or homework. However, learning to program requires lots of hands on practice. We encourage everyone to work through the provided practice problems and/or practice applying the skills to your own research throughout the semester.
I can’t attend in person. Is there a virtual option?
Unfortunately, we are not able to offer a synchronous virtual option this year. However, each week we will post all of the materials (practice questions, demos, answer keys etc.) and a recording of the live session for those who want to follow along asynchronously.
If you are not able to attend live but are interested in the course make sure to subscribe to our mailing list and join our slack channel to keep up with course updates and the QuACK community.