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Handbook 1997 : Faculty of Science : Statistics

619-230 Sampling, Simulation and Resampling

Credit Points:

12.5

Coordinator:

Professor T C Brown

Prerequisite/s:

One of 615-160 or 617-141 or 619-100 plus a 100 level Mathematics subject. (Prior to 1996, 617-160 = 617-141).

Timetable:

Semester 2

Contact:

39 lectures (three a week) and 26 tutorial/practice class hours

Objectives:

Students completing this course should:

Comprehend:

  • the concepts of randomness, sampling and simulation;

  • the choice of an efficient sampling method.

Have developed the skills:

  • to administer and analyse a simple sample survey;

  • to select a random sample;

  • to simulate sampling from a population;

  • to use resampling as an inference tool.

Appreciate:

  • the breadth of application of simulation techniques to diverse problems in operations research, probability and statistics;

  • the principles of sampling methods;

  • the usefulness of resampling methods in statistical inference.

Content:

Sampling Samples and their properties. Using population characteristics to improve sampling efficiency: stratified sampling. Sampling from a finite population: finite population correction.Simulation Uniform number generators. Tests for randomness. Generating numbers from other distributions. Simulating random samples. Dependent variables. Monte Carlo methods. ResamplingSimulation testing: randomisation tests, Monte Carlo tests. Bootstrap methods: sampling and bootstrap distributions; parametric bootstrap.

Assessment:

A 2 hour end-of- semester written examination; written Simulation project worth 15% (up to 10 pages); three written assignments during the semester worth 15% (total 12 pages); participation in tutorials worth 5% (assessed through formal presentations in tutorials.
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Handbook 1997 : Faculty of Science : Statistics 
Status:                   OFFICIAL 1997
Last Modified:            Wednesday March 12 3:36 pm
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Copyright © University of Melbourne 1997.