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302315 (v.2) Mathematical Statistics 202
Area: | Department of Mathematics and Statistics |
Credits: | 25.0 |
Contact Hours: | 4.0 |
Lecture: | 1 x 3 Hours Weekly |
Workshop: | 1 x 1 Hours Weekly |
Prerequisite(s): | 7062 (v.6) Mathematics 101 or any previous version
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7149 (v.7) Principles of Statistics 101 or any previous version
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Syllabus: | Probability theory, special univariate distributions, multivariate, marginal and conditional distributions, introduction to stochastic processes, Markov chain, expectation and generating functions, functions of random variables and derived distributions,random sums, convergence of random sequence, sampling distributions, basic methods of estimation (MLE and MME), unbiasedness and consistency, introduction to decision theory, Minimax approach and Bayes approach, structure of Bayes rule, complete class ofrules, construction of minimax rules, point and interval estimations as a decision problem, hypothesis testing as a decision problem. |
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Unit Outcomes: | This unit is designed to give you theoretical aspects of statistics. On successful completion of this unit you will be able to identify the role of probability theory in statistical methods. Gain in depth knowledge of some basic and advanced concepts in probability theory. Demonstrate an understanding of the basic probability concepts in modeling real life situations. Distinguish between the different types of probability distributions and their applicability in real world. Demonstrate knowledge of dealing with more than one random variables and their applications. Demonstrate basic knowledge in Bayesian Methods. Demonstrate knowledge of using computer simulation to study real world situations. |
Texts and references listed below are for your information only and current as of September 30, 2003. Some units taught offshore are modified at selected locations. Please check with the unit coordinator for up-to-date information and approved offshore variations to unit information before finalising study and textbook purchases. |
Unit References: | Hoel, P.G., Port, S.C. & Stone, C.J. (1971) Introduction to Probability Theory Houghton Mifflin, Boston. Rice, John A. (1995) Mathematical Statistics and Data Analysis, Duxbury. Cassella, G., Berger, R.L. 1990 Statistical Inference Duxbury Press. Freund, John. (1992) Mathematical Statistics, Prentice Hall. Snell, Laurie (1988) Introduction to Probability, Random House/Birkhauser, New York. Dudewicz, E.J. & Mishra, S.N. (1988) Modern Mathematical Statistics, John Wiley. Feller, W. (1968) An Introduction to Probability and its Applications Volume 1, 3rd Edition. |
Unit Texts: | Probability and Statistics (2002) 3rd edition Morris H. DeGroot and Mark J. Schervish. Addison Wesley. |
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Unit Assessment Breakdown: | Test (1) 10%. Assignment (2) 20%. Final Exam 70%. This is by grade/mark assessment. |
Field of Education: | 10100 Mathematical Sciences (Narrow Grouping) | HECS Band (if applicable): | 2 |
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Extent to which this unit or thesis utilises online information: | Not Online | Result Type: | Grade/Mark |
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Availability
| Year | Location | Period | Internal | Area External | Central External | | 2004 | Bentley Campus | Semester 2 | Y | | |
Area
External | refers to external course/units run by the School or Department, offered online or through Web CT, or offered by research. |
Central
External | refers to external course/units run through the Curtin Bentley-based Distance Education Area |
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