• 1. Introduction
• 2. How do I get started?
• 3. Common analysis steps
  • 3.1. I. Reading raw data
    • 3.1.1. An aside about file paths
  • 3.2. II. Cleaning up and preprocessing raw data
  • 3.3. III. Aggregate raw data
  • 3.4. IV. Descriptive analysis and plots
    • 3.4.1. Descriptive stastics: Getting a sense of your data
    • 3.4.2. Confidence intervals
    • 3.4.3. Data visualisation magic
      • 3.4.3.1. Boxplots
      • 3.4.3.2. Adding titles and labels
      • 3.4.3.3. Spaghetti plots
      • 3.4.3.4. Fancy Barplots
      • 3.4.3.5. Visualizing correlations with scatter plots
  • 3.5. V. Inferential analysis
    • 3.5.1. Normality assumption
    • 3.5.2. Homogeneity of variance assumption
    • 3.5.3. Correlation
    • 3.5.4. Regression
    • 3.5.5. t-test
    • 3.5.6. One-way ANOVA
    • 3.5.7. Repeated measures ANOVA
    • 3.5.8. Mixed designs (within/between factors)
• 4. General notes on R |
  • 4.1. Interface
  • 4.2. Install and import packages
  • 4.3. Let’s start and create a few objects
    • 4.3.1. First objects in R
    • 4.3.2. Arithmetic operations
    • 4.3.3. Let’s turn to somewhat more advanced stuff
  • 4.4. What are if statements?
  • 4.5. And what about loops?

Introduction

Dear students,