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
16.
One-Sample Tests
16.1.
One-Sample t-test
16.1.1.
Assumptions
16.1.2.
Test Statistic
16.1.3.
Degrees of Freedom
16.1.4.
Implementation in R
16.1.5.
Interpretation
16.2.
One-Sample z-test
16.2.1.
When to Use
16.2.2.
Test Statistic
16.2.3.
Implementation
16.3.
One-Sample Proportion Test
16.3.1.
Assumptions
16.3.2.
Test Statistic
16.3.3.
Normal Approximation
16.3.4.
Implementation in R
16.4.
Tests for Variance
16.4.1.
Chi-squared Test
16.4.2.
Assumptions
16.4.3.
Implementation
16.5.
Nonparametric One-Sample Tests
16.5.1.
Sign Test
16.5.2.
Wilcoxon Signed-Rank Test
16.5.3.
When to Use Nonparametric Tests
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15. Hypothesis Testing Framework
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17. Two-Sample Tests