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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
2.
R Fundamentals and Basic Operations
2.1.
R as a Calculator
2.1.1.
Arithmetic Operations
2.1.2.
Order of Operations
2.1.3.
Mathematical Functions
2.1.4.
Scientific Notation
2.2.
Variables and Assignment
2.2.1.
Assignment Operators
2.2.2.
Variable Naming Rules
2.2.3.
Variable Naming Conventions
2.2.4.
Case Sensitivity
2.3.
Understanding R Functions
2.3.1.
Function Syntax
2.3.2.
Arguments and Parameters
2.3.3.
Default Arguments
2.3.4.
Named Arguments
2.3.5.
Nested Function Calls
2.4.
Getting Help in R
2.4.1.
help() Function
2.4.2.
? Operator
2.4.3.
?? Operator for Fuzzy Search
2.4.4.
example() Function
2.4.5.
vignette() Function
2.4.6.
Online Documentation
2.5.
R Workspace Management
2.5.1.
Working Directory Concepts
2.5.2.
getwd() and setwd()
2.5.3.
Listing Objects
2.5.4.
Removing Objects
2.5.5.
Saving and Loading Workspaces
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3. R Package System