620-374 Sampling and Forecasting

Credit Points

12.5

Coordinator

Dr O Jones

Prerequisites

620-202

Semester

2 (view timetable)

Contact

36 lectures (three per week) and up to 12 practice classes (1 per week)

Subject Description

This subject covers a range of important and generally applicable statistical methods.

Students should develop the ability to employ these methods to implement a range of practically useful statistical analyses. The following three topics will be covered:

  • sample surveys: simple random sampling; stratified sampling - optimal allocation, post-stratification; cluster sampling; ratio estimation;

  • time series and forecasting: patterns in time series; simple methods for exploratory data analysis; smoothing techniques; decomposition, trends and seasonal variation; simple forecasting methods; models for time series: stationarity, autocorrelation, ARMA processes; estimation and model fitting; and

  • re-sampling methods: jack-knife and the bootstrap; and use of the bootstrap for exploring the sampling distribution of an estimator.

Assessment

Up to 50 pages of written assignments during the semester (20%); a 3-hour written examination in the examination period (80%).



Status:                   Official 2007
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