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
13.
Sampling and Sampling Distributions
13.1.
Sampling Concepts
13.1.1.
Population vs Sample
13.1.2.
Sampling Frame
13.1.3.
Sampling Units
13.1.4.
Sample Size Considerations
13.2.
Sampling Methods
13.2.1.
Probability Sampling
13.2.1.1.
Simple Random Sampling
13.2.1.2.
Systematic Sampling
13.2.1.3.
Stratified Sampling
13.2.1.4.
Cluster Sampling
13.2.2.
Non-probability Sampling
13.2.2.1.
Convenience Sampling
13.2.2.2.
Purposive Sampling
13.2.2.3.
Quota Sampling
13.2.3.
Sampling Bias
13.3.
Sampling Distributions
13.3.1.
Concept of Sampling Distribution
13.3.2.
Sampling Distribution of the Mean
13.3.3.
Sampling Distribution of Proportions
13.3.4.
Standard Error
13.4.
Central Limit Theorem
13.4.1.
Theorem Statement
13.4.2.
Conditions and Applications
13.4.3.
Normal Approximation
13.4.4.
Sample Size Effects
13.5.
Simulation in R
13.5.1.
Random Sampling
13.5.2.
Bootstrap Sampling
13.5.3.
Monte Carlo Methods
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14. Statistical Inference Foundations