Semester 1, 2018

MAST20006 - Probability for Statistics Notes

41 pages

9,085 words




This is a comprehensive compilation of information from MAST20009 lectures, the textbook, tutorials, practicals, workshops, problem booklets and other useful sources I found online to aid my study.

Each section (particularly the harder concepts) is supported by easy to read and understand dot points, diagrams, pictures and thorough example exam-style questions.

Includes all summarised formulae required to know for each topic.

Topics included are:
1. Classic probability model (Bayes' Theorem, conditional probability, relative frequency)
2. Discrete distributions (pmf, binomial, negative binomial, hypergeometric, geometric, poisson, uniform, mgf's)
3. Continuous distributions (definitions, pdf, cdf, exponential, gamma, chi-square, uniform and beta distributions)
4. Multivariate distributions (marginal and joint pdf/pmf, multivariate transformations, independent random variables)
5. Normal distribution (summary of normal distribution, mgf, approximations of discrete distributions using normal, limiting mgf functions).