Lectures related to Binomial distribution

Binary Covariate Impact: 2x2 Contingency Tables

Explores the impact of a binary covariate on binary responses using 2x2 tables.

Delves into probability, statistics, paradoxes, and random variables, showcasing their real-world applications and properties.

Statistical Models: Basics & Applications

Covers statistical concepts like probability, estimation, hypothesis testing, and confidence intervals for mathematicians.

Common Distributions: Moment Generating Functions

Explores common probability distributions, special distributions, and entropy concepts.

Advanced Probabilities: Random Variables & Expected Values

Explores advanced probabilities, random variables, and expected values, with practical examples and quizzes to reinforce learning.

Random Walk and Diffusion: Basics and Applications

Introduces random walk, diffusion, binomial distribution, and the master equation.

Random Variables: Expected Value

Covers advanced probability concepts, including random variables and expected value calculation.

Random Variables and Expected Value

Introduces random variables, probability distributions, and expected values through practical examples.

Bayes' Theorem: Defective Parts Detection

Explores Bayes' Theorem for defective parts detection, discrete random variables, and distribution functions, with practical examples and exercises.

Discrete Random Variables: Functions and Distributions

Introduces probability mass functions for discrete random variables and various distributions, emphasizing the calculation of expectations.

Confidence Intervals: Student, Asymptotic Wald

Covers confidence intervals for Gaussian means, Student distribution, and Wald confidence intervals for maximum likelihood estimators.

Elementary Distributions Factsheet

Covers elementary distributions like Bernoulli, Binomial, Geometric, Negative Binomial, Poisson, and Multinomial.

Common Distributions: Moments and MGFs

Covers common distributions, moment generating functions, and covariance matrices in statistics for data science.

ANOVA: Partitioning Total SS

Covers ANOVA method, focusing on partitioning total sum of squares into treatment and error components, mean square calculations, Fisher statistic, and F-distribution.

Probability and Statistics: Discrete Random Variables

Explores discrete random variables, mass functions, and distribution functions in probability and statistics.

Advanced Probability

Delves into advanced probability theory, covering inequalities, trials, distributions, and calculations for probabilities and expectations.

Probability: Bernoulli Trials

Explores Bernoulli trials, independent trials, and the binomial distribution.

Advanced Probability: Probability Trees and Conditional Probabilities

Explores probability trees, conditional probabilities, Bernoulli trials, binomial distribution, and Bayes' Theorem.

Combinatorial Mathematics

Explores combinatorial mathematics, covering permutations, combinations, and binomial coefficients, along with probability and statistics concepts.

Stochastic Models for Communications

Covers stochastic models for communications, focusing on random variables, Markov chains, Poisson processes, and probability calculations.