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
Probability Theory
Fundamental Concepts
Random Experiments
Sample Spaces
Events
Probability Definitions
Classical Probability
Relative Frequency
Subjective Probability
Probability Rules
Addition Rule
Multiplication Rule
Complement Rule
Conditional Probability
Independence
Mutually Exclusive Events
Bayes' Theorem
Theorem Statement
Prior and Posterior Probabilities
Counting Principles
Permutations
Combinations
Factorial Notation
Random Variables
Definition and Types
Discrete Random Variables
Continuous Random Variables
Probability Functions
Probability Mass Functions
Probability Density Functions
Cumulative Distribution Functions
Expected Value and Variance
Expected Value
Variance and Standard Deviation
Properties of Expected Value
Properties of Variance
Previous
10. Advanced Data Visualization with ggplot2
Go to top
Next
12. Probability Distributions