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Related lectures (31)

Page 2 of 4

Probability and Statistics: Fundamental Theorems

Explores fundamental theorems in probability and statistics, joint probability laws, and marginal distributions.

Discrete Random Variables: Functions and Distributions

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

Common Distributions: Moments and MGFs

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

Common Distributions: Moment Generating Functions

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

Elementary Distributions Factsheet

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

Probability and Statistics

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

Geometric and Negative Binomial Distributions

Explains the geometric and negative binomial distributions and their properties.

Advanced Probability

Covers advanced topics in probability theory, focusing on geometric distribution and variance calculations.

Robotics Kinematics

Covers rotation matrices, translations, and direct geometric modeling of serial robots, including the Denavit-Hartenberg parameters and the sequence of movements for a 6 DOF robot.

Binomial and Poisson Mass Functions

Explores binomial and Poisson mass functions, calculating probabilities and discussing distribution functions of random variables.