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
Data Import and Export
File System Navigation
Working Directory
File Paths
Relative vs Absolute Paths
Importing Delimited Files
CSV Files
read.csv() Function
read.table() Function
readr::read_csv() Function
Tab-delimited Files
Custom Delimiters
Handling Headers
Specifying Data Types
Handling Missing Values
Character Encoding
Importing Excel Files
readxl Package
read_excel() Function
Sheet Selection
Range Selection
openxlsx Package
Handling Multiple Sheets
Importing from Statistical Software
haven Package
SPSS Files
Stata Files
SAS Files
foreign Package
Preserving Labels and Attributes
Database Connections
DBI Package
RSQLite Package
Connecting to Databases
SQL Queries in R
ODBC Connections
Web Data Import
Reading from URLs
Web Scraping Basics
API Data Access
Exporting Data
Writing CSV Files
write.csv() Function
write.table() Function
readr::write_csv() Function
Exporting to Excel
writexl Package
openxlsx Package
Saving R Objects
save() Function
saveRDS() Function
load() Function
readRDS() Function
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6. Data Cleaning and Preprocessing