UsefulLinks
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
27.
Introduction to Machine Learning
27.1.
Machine Learning Overview
27.1.1.
Supervised Learning
27.1.2.
Unsupervised Learning
27.1.3.
Reinforcement Learning
27.2.
Classification vs Regression
27.2.1.
Problem Types
27.2.2.
Evaluation Metrics
27.3.
Training and Testing
27.3.1.
Train-Test Split
27.3.2.
Cross-validation
27.3.3.
Overfitting and Underfitting
27.4.
Decision Trees
27.4.1.
Tree Construction
27.4.2.
Splitting Criteria
27.4.3.
Pruning
27.4.4.
Implementation in R
27.5.
Model Evaluation
27.5.1.
Confusion Matrix
27.5.2.
Accuracy Metrics
27.5.3.
ROC Curves
27.5.4.
Cross-validation
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28. Reproducible Research