In this repository, I will delve into the fundamental concepts of statistics and probability through the use of Python programming language. The following topics will be covered:
- Permutations and Combinations
- The basics of probability, including conditional probability and the law of large numbers
- Bayes' theorem and its applications
- Probability distributions, including binomial, uniform, geometric, Poisson, and normal distributions
- Measures of central tendency and variability, as well as skewness and kurtosis
- The central limit theorem, estimation, and confidence intervals
- Sampling methods and errors
- Hypothesis testing, significance levels, P values, and confidence intervals
- Parametric tests, including z-tests (one-tailed and two-tailed) for means and proportions and t-tests (paired t-test)
- Analysis of variance (ANOVA)
- Nonparametric tests, such as chi-square tests
- Effect size, correlation, power, and power analysis.