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
Hypothesis Testing Framework
Hypothesis Testing Logic
Scientific Method
Statistical Hypotheses
Null and Alternative Hypotheses
One-tailed vs Two-tailed Tests
Test Statistics
Standardized Test Statistics
Sampling Distribution Under Null
Critical Values
Decision Making
Rejection Regions
p-values
Significance Levels
Statistical vs Practical Significance
Types of Errors
Type I Error
Type II Error
Power of a Test
Relationship Between Errors
Steps in Hypothesis Testing
State Hypotheses
Choose Significance Level
Select Test Statistic
Determine Critical Value
Calculate Test Statistic
Make Decision
Draw Conclusion
Previous
14. Statistical Inference Foundations
Go to top
Next
16. One-Sample Tests