Statistical Inference: Random Variables

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

Probability Theory: Midterm Solutions

Covers the solutions to the midterm exam of a Probability Theory course, including calculations of probabilities and expectations.

Linear Combinations: Moment-Generating Functions

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

Introduction to Continuous Random Variables: Probability Distributions

Introduces continuous random variables and their probability distributions, emphasizing their applications in statistics and data science.

Probability Models: Fundamentals

Introduces the basics of probability models, covering random variables, distributions, and statistical estimation.

Random Vectors and Stochastic Models for Communications

Covers random vectors, joint probability, and conditional probability in communication stochastic models.

Normal Distribution: Properties and Calculations

Covers the normal distribution, including its properties and calculations.

Probability and Stochastic Processes: Fundamentals and Applications

Discusses the fundamentals of probability and stochastic processes, focusing on random variables, their properties, and applications in statistical signal processing.

Random Variables: Expectation and Independence

Explores random variables, expectation, and independence in probability theory.

Families of Distributions: PDFs and CDFs

Explores PDFs and CDFs for discrete and continuous random variables, including Gaussian, uniform, and exponential distributions.