• Front Matter
  • Welcome to PSY 310
    • Mason Notes
      • How to use these notes
  • Attribution
    • Major Attributions
    • Additional Attributions
  • License
  • Colophon
  • I Module 00
  • Don’t Miss Module 00
    • 0.1 Learning Goals for this Module (Chapter 0)
    • 0.2 To-Do List
    • 0.3 Course Modality
  • 1 Knowledge is Power
    • 1.1 Meet Prof. Mason
    • 1.2 Website Tour
  • Guidance
    • 1.3 Syllabus
    • 1.4 Materials
      • 1.4.1 Hardware
      • 1.4.2 Required Texts
      • 1.4.3 Software
  • II Module 06
  • 2 Welcome to Probability
    • 2.1 Basic Probability Concepts
      • 2.1.1 What is probability?
      • 2.1.2 The Probability Formula
    • 2.2 Probability & Frequency Distributions
    • 2.3 Probability in Normal Distributions
    • 2.4 Considerations in understanding probability and inferential statistics: sampling
    • 2.5 More Probability Terms
      • 2.5.1 Statistical Independence
    • 2.6 Recap
      • 2.6.1 Learning objectives
      • 2.6.2 Exercises
  • III Module 07
  • 3 Welcome to Sampling and some more on probability
    • 3.1 How are probability and statistics different?
    • 3.2 What does probability mean?
      • 3.2.1 The frequentist view
      • 3.2.2 The Bayesian view
      • 3.2.3 What’s the difference? And who is right?
    • 3.3 Basic probability theory
      • 3.3.1 Introducing probability distributions
    • 3.4 The binomial distribution
      • 3.4.1 Introducing the binomial
      • 3.4.2 Working with the binomial distribution in R
    • 3.5 The normal distribution
      • 3.5.1 Probability density
    • 3.6 Other useful distributions
    • 3.7 Summary
  • IV Other Coolness
  • 4 Good Resources
  • 5 Media without a home yet
    • 5.1 Visualizing Linear Models: An R Bag of Tricks
    • 5.2 For new programmers learning keyboard shortcuts…
    • 5.3 Are you a student? If yes, this is the best data science project for you!
    • 5.4 rstudio is magic
    • 5.5 automation quote
    • 5.6 How computer memory works!
    • 5.7 Is Coding a Math Skill or a Language Skill? Neither? Both?
    • 5.8 Quantum Computers Explained!
    • 5.9 The Rise of the Machines – Why Automation is Different this Time
    • 5.10 Who Would Be King of America if George Washington had been made a monarch?
    • 5.11 Emergence – How Stupid Things Become Smart Together
    • 5.12 The Birthday Paradox
    • 5.13 Why can’t you divide by zero?
    • 5.14 Yea he’s chewing up my stats homework but that face though…
    • 5.15 Coding Kitty
    • 5.16 Democratic databases: science on GitHub
    • 5.17 Ten simple rules for getting started on Twitter as a scientist
    • 5.18 NYT data ethics stuff
    • 5.19
  • References
  • License: CC-BY-SA

Psychology Research Methods

4 Good Resources

  • https://psychnerdjae.github.io/into-the-tidyverse/
  • Automatic Grading with RMarkdown example
  • Git/Github for virtual learning (from this tweet)
  • Learn-Datascience-for-Free
  • https://allisonhorst.shinyapps.io/dplyr-learnr/
  • Visualizing Linear Models: An R Bag of Tricks