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
Two-Sample Tests
Independent Samples t-test
Assumptions
Equal Variances
Unequal Variances
Welch's t-test
Implementation in R
Effect Size
Paired Samples t-test
When to Use
Assumptions
Test Statistic
Implementation in R
Comparison with Independent Samples
Two-Sample Proportion Test
Assumptions
Test Statistic
Implementation in R
Fisher's Exact Test
Tests for Equal Variances
F-test
Levene's Test
Bartlett's Test
Nonparametric Two-Sample Tests
Mann-Whitney U Test
Wilcoxon Rank-Sum Test
Kolmogorov-Smirnov Test
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16. One-Sample Tests
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18. Chi-squared Tests