Ch. 14 Workshops

Intro to Reproducible Science: July 6, 8, 11th, 2022; 11am to 2pm
- Submit Questions: Submit your questions here
- Location: In person at UCF; in PSY301Q
- Format: Live, with recordings available for later viewing.
- Objectives
  - Describe various tools and techniques supportive of open and reproducible science.
  - List and describe the FAIR Principles (https://www.go-fair.org/fair-principles)
  - Develop a code-only pipeline to allow reproducibility of data prep and analyses.
  - Develop a long-term learning plan for practicing reproducible science tools and techniques.
- Day 1
  - What is Reproducible Science?
  - Reproducible & FAIR Data Workflows
  - Tools Supporting Reproducible Science
  - Overview of available tools
    - Skill 1: Using Endnote for Reference Management
    - Skill 2: Using Git (and Github) for code management and collaboration
  - Orientation to R, RStudio, RMarkdown
    - Skill 3: R syntax primer
  - Data Science: Latest trends
  - Long-term Learning Recommendations
- Day 2
  - Data wrangling and visualization of Big Data
    - Skill 1: Data wrangling the Google Mobility dataset
  - Reproducible survey research
    - Qualtrics survey design tips
    - Skill 2: Data wrangling Qualtrics data
  - Working with JSON data
    - Skill 3: cleaning and visualizing keystroke JSON data
- Day 3
  - Text mining
    - Skill 1: word and bigram frequency analysis
    - Skill 2: generating wordclouds
    - Skill 3: sentiment analysis
  - Interacting with APIs and JSON data
    - Skill 4: querying API for results and data aggregation
  - Closing Discussion & Q/A

13 Resources

15 Recordings