Probability for Statistics is a mathematically rigorous subject that builds a strong theoretical foundation for statistical modeling and inference. It covers combinatorics, discrete and continuous distributions, expectation, variance, moment generating functions, joint distributions, and limit theorems. The subject is proof-heavy and abstract at times, but highly rewarding if you enjoy mathematical thinking. It’s essential for anyone aiming to do advanced statistics, data science, or econometrics. Tutorials are helpful, and consistent practice is crucial to keep up with the pace.

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Too easy. Need some tricks.

Good subject, relatively easy for a university math subject.

Introduces the basics of probability very well, but the lecturer needs to be more clear on what is expected.

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