Welcome to the Statistics for Data Science repository! This repository is dedicated to providing structured and well-explained statistical concepts, ranging from basics to advanced techniques, with examples and real-world applications.
Statistics is the study of the collection, analysis, interpretation, presentation, and organization of data. Provides tools and methods to understand and analyze data patterns, make predictions, and inform decision-making.
- Descriptive Statistics: Mean, Median, Mode, Variance, Standard Deviation
- Probability Theory: Probability Distributions, Bayes' Theorem
- Inferential Statistics: Hypothesis Testing, Confidence Intervals, p-values
- Regression Analysis: Linear Regression, Logistic Regression
- Statistical Tests: t-test, ANOVA, Chi-Square test
- Time Series Analysis: Moving Averages, ARIMA, Exponential Smoothing
- Machine Learning & Statistics: Feature Engineering, Statistical Modeling
