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MATH3811 Statistical Inference MATH3811 is a Mathematics Level III course. See the course overview below. Units of credit: 6 Prerequisites: MATH2831 or MATH2931 Exclusions: MATH3840, MATH3850, MATH3911, MATH3940, MATH3950. Cycle of offering: yearly in Semester 1. Graduate attributes: the course will enhance your research, inquiry and analytical thinking abilities. More information: this recent course handout (pdf) contains information about course objectives, assessment, course materials and the syllabus. (This pdf will usually be updated by the end of the first week of the semester.) The Online Handbook entry contains up-to-date timetabling information. If you are currently enrolled in MATH3811, you can log into the My eLearning Vista instance of this course. Course Overview This course studies the fundamentals of Statistics Inference and teaches you how to draw the right conclusions and interpretations about a model that has generated your data set. In this course you will learn which are the most efficient statistical inference procedures used in practice and will understand in what sense these procedures are considered to be efficient. MATH3811/MATH3911 is a core course of a Statistics major. The course will cover a variety of topics including: uniformly minimum variance estimation; Cramer-Rao inequality and Lehmann-Scheffe theorem; Monotone likelihood ratio distributions and uniformly most powerful unbiased tests; Generalised likelihood ratio tests; Bayesian point estimation and hypothesis testing; Robustness and bootstrap resampling; Order statistics, goodness of fit, contingency tables; Statistical inference based on ranks; One sample, two sample and k-sample non-parametric problems; independence and measures of association. |
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AUTHORISED BY Head, School of Mathematics and Statistics Page last updated: Monday, March 3rd, 2008 |
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