Statistics & Probability

Essential concepts and applications of statistics, probabilities, including distributions, Bayesian inference, and Monte Carlo methods.

Snippets

• Bayes' Theorem & Applications
  Bayesian inference and practical applications
• Central Limit Theorem
  Foundation of statistical inference
• Common Probability Distributions
  Normal, Binomial, Poisson, Exponential, Gamma, Pareto distributions
• Monte Carlo Methods
  Simulation and numerical integration
• Null Hypothesis Testing
  Understanding null hypothesis and hypothesis testing
• P-Values Explained
  Understanding p-values and statistical significance
• Percentiles and Quantiles
  Understanding percentiles, quartiles, and quantiles
• Probability Basics
  Fundamental probability concepts and rules
• Random Variables
  Expected value, variance, and moments
• Statistical Moments
  Mean, variance, skewness, and kurtosis explained