Lectures related to Coin flipping

Advanced Probabilities: Random Variables & Expected Values

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

Random Variables and Expected Value

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

Solving Equations with Irrational Parametric Inequalities

Covers solving equations and inequalities with irrational parameters using step-by-step examples.

Binomial Distribution in R

Introduces the Binomial distribution in R with examples of n coin tosses.

Random Variables: Basics and Examples

Explains random variables, distributions, and Bernoulli trials with coin flip examples.

Infinite Coin Tosses: Independence

Explores independence in infinite coin tosses, covering sets, shifts, and T-invariance.

Extension of the Weak Law: St. Petersburg's Paradox

Explores the extension of the weak law of large numbers using St. Petersburg's paradox as an example.

Statistical Hypothesis Testing

Covers statistical hypothesis testing, confidence intervals, p-values, and significance levels in hypothesis testing.

Interpretation of Entropy

Explores the concept of entropy expressed in bits and its relation to probability distributions, focusing on information gain and loss in various scenarios.

Random Variables: Expected Value

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

Advanced Probability: Examples

Covers the Geometric Distribution, biased coins, expected number of flips, and generating random numbers.

Binomial Distributions

Covers the normal distribution, inferential statistics, probability, and the binomial distribution in the context of the 'Dishonest Gambler Problem'.

Discrete Random Variables: Functions and Probabilities

Explores discrete random variables, their functions, and probabilities in various scenarios.

Probability Laws and Event Spaces

Explains probability laws, event spaces, and confidence levels in event occurrences.

Risk and Risk Premium

Explores risk evaluation, equivalent value, and insurance premium in lotteries, as well as discount rate adjustments.

Probability Theory: Random Variables and Codes

Explores probability theory, random variables, and codes applications in games.

Advanced Probability: Bayes' Theorem and Random Variables

Covers advanced probability concepts, including Bayes' Theorem and Random Variables.

Conditional Probability: Basics and Examples

Explains conditional probability through dice and coin examples.

Smart Contract Implementation: Coin

Covers the implementation of a smart contract for a simple coin and discusses financial blockchain applications.

Probability & Stochastic Processes

Covers applied probability, stochastic processes, Markov chains, rejection sampling, and Bayesian inference methods.