This repository contains materials and code related to a week-long study of statistics. The content covers fundamental concepts in statistics, including descriptive statistics, inferential statistics, and various statistical techniques. The content is organized into daily sessions.
- Day 1: Introduction to Statistics
- Day 2: Measures of Central Tendency and Dispersion
- Day 3: Distributions and Normal Distribution
- Day 4: Outliers Detection
- Definition of Statistics
- Types of Statistics: Descriptive and Inferential
- Descriptive Statistics:
- Measures of Central Tendency (Mean, Median, Mode)
- Measures of Variance (Standard Deviation, Variance, Range, Interquartile Range)
- Population and Samples
- Sampling Techniques
- Types of Variables
- Impact of Outliers on Mean, Median, and Mode
- Experiment with Outliers
- Percentiles and Quartiles
- Five-Number Summary
- Boxplots for Outliers Detection
- Understanding Normal Distribution
- Properties of Normal Distributions
- Empirical Rule
- Standard Normal Distribution
- Calculating Z-Scores
- Using Z-Scores for Standardization
- Example: Finding Percentiles
- Identifying Outliers Using 3rd Standard Deviation
- Adding Outliers to Data
- Function for Outliers Detection
Feel free to use the provided R code and examples for learning or teaching statistics. Each day's content is organized in separate R scripts for clarity.