R

Introduction to R

1. R and RStudio
2. Comments, Variables and Data Types
3. Packages and Libraries
4. Maths and Numbers
5. Strings and Characters
6. Vectors
7. Named Vectors and Lists (aka Dictionaries)
8. Booleans and If Statements
9. Data Frames
10. For and While Loops
11. Functions
12. Exception Handling
13. Linting
14. Python in R

Working with Data

1. Pre-Loaded Datasets
2. Create Unique Identifiers
3. Data Stratification
   • Data Classification Using Date or Time Information
4. Filter by Number of Times a Values Appears
5. Descriptive and Summary Statistics
6. Pivot Tables
7. Demographic Data Tables
8. Merging
9. File IO: Create, Export and Import Data
10. Filling in Missing Data
11. Working with JSON Files

Graphs

1. Using Base R
   • Symbols, Line Types and Colours
   • Line Plots
   • Scatter Plots
   • Bland-Altman Plots
   • Box Plots (Box-and-Whisker Plots):
     • Single Group
     • Multiple Groups
   • Bee Swarm Plots
   • Bar Plots:
     • Single Factor
     • Multiple Factors
   • Receiver Operating Characteristic (ROC) Curves
2. Using ggplot2
   • Cheat Sheet
   • Line Plots
   • Scatter Plots
   • Bland-Altman Plots
   • Box Plots (Box-and-Whisker Plots):
     • Single Group
     • Multiple Groups
   • Bar Plots:
     • Single Factor
     • Multiple Factors
   • Receiver Operating Characteristic (ROC) Curves

Statistics

1. Descriptive Statistics
2. Diagnostic Accuracy Tutorial (complete, empty)
3. Principal Component Analysis
4. Hypothesis Testing:
   • Kruskal-Wallis Rank Sum Test
   • Friedman Rank Sum Test
   • Chi-Squared Tests
5. Agreement (Accuracy & Precision):
   • Passing–Bablok Regression
   • Repeatability Coefficient
   • Bland-Altman and Giavarina Analysis
   • Coefficient of Variation