Probability Fundamentals

Related lectures (30)

Page 3 of 3

Covers the calculation of expectation and variance for different types of random variables, including discrete and continuous ones.

Covers Simpson's paradox, probability distributions, and real-life examples in probability and statistics.

Explores continuous random variables and their properties, including support and cumulative distribution functions.

Covers the basics of probability theory, random variables, joint probability, and inference.

Explores moment-generating functions, linear combinations, and normality of random variables.

Covers probability, statistics, independence, covariance, correlation, and random variables.

Covers properties and calculations related to the normal distribution, including probabilities and quantiles.

Covers conditional probability distributions and introduces the concept of conditional expected value.

Covers fundamental concepts in probability and statistics, including distributions, properties, and expectations of random variables.

Introduces statistical modelling basics, probability theory, and key concepts for data science applications.