Probability and Distribution Theory (BSTA5023)


This unit begins with the study of probability, random variables, discrete and continuous distributions, and the use of calculus to obtain expressions for parameters of these distributions such as the mean and variance. Joint distributions for multiple random variables are introduced together with the important concepts of independence, correlation and covariance, marginal and conditional distributions. Techniques for determining distributions of transformations of random variables are discussed. The concept of the sampling distribution and standard error of an estimator of a parameter is presented, together with key properties of estimators. Large sample results concerning the properties of estimators are presented with emphasis on the central role of the Normal distribution in these results. General approaches to obtaining estimators of parameters are introduced. Numerical simulation and graphing with Stata is used throughout to demonstrate concepts.

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Further unit of study information


8-12 hours total study time per week, distance learning


practical exercises (30%) and 2xwritten assignments (2x35%)


Wackerly DO, Mendenhall W, Scheaffer RL. Mathematical Statistics with Applications, 7th edition, 2008, Brooks/Cole, Cengage Learning, USA. ISBN 978-0-495-11081-1 Notes supplied

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If you wish to undertake one or more units of study (subjects) for your own interest but not towards a degree, you may enrol in single units as a non-award student.

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