Useful Links
Statistics
Statistics with R
1. Introduction to R and Statistical Computing
2. R Fundamentals and Basic Operations
3. R Package System
4. R Data Structures
5. Data Import and Export
6. Data Cleaning and Preprocessing
7. Data Manipulation with dplyr
8. Descriptive Statistics
9. Data Visualization Fundamentals
10. Advanced Data Visualization with ggplot2
11. Probability Theory
12. Probability Distributions
13. Sampling and Sampling Distributions
14. Statistical Inference Foundations
15. Hypothesis Testing Framework
16. One-Sample Tests
17. Two-Sample Tests
18. Chi-squared Tests
19. Analysis of Variance (ANOVA)
20. Correlation Analysis
21. Simple Linear Regression
22. Regression Diagnostics
23. Multiple Linear Regression
24. Generalized Linear Models
25. Nonparametric Statistics
26. Introduction to Time Series Analysis
27. Introduction to Machine Learning
28. Reproducible Research
29. Statistical Computing Best Practices
R Package System
Understanding Packages
What are R Packages
Package Structure
Package Dependencies
Package Namespaces
Installing Packages
install.packages() Function
Installing from CRAN
Installing from GitHub
Installing from Local Files
Package Version Management
Loading and Using Packages
library() Function
require() Function
Differences Between library() and require()
Package Conflicts
Detaching Packages
Package Management
Updating Packages
Removing Packages
Checking Installed Packages
Package Dependencies
The Tidyverse Ecosystem
Overview of Tidyverse Philosophy
Core Tidyverse Packages
Installing Tidyverse
Loading Tidyverse
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4. R Data Structures