620-270 Applied Statistics

Note

Credit Points

HECS Band

Coordinator

Prerequisites

One of 620-131, 620-152, 620-160.

Semester

Contact

Subject Description

This subject demonstrates the importance of statistical methods for interpreting data, the role of exploratory and formal data analysis and the importance of experimental design. Students should learn to examine data to determine underlying structures, formulate statistical models for a range of practical situations and check the assumptions of the model in specific situations. They should also learn to use the computer to carry out standard statistical analyses and to express conclusions in scientifically useful terms.

Introduction to statistical inference: estimation; confidence intervals; hypothesis testing including the power of tests, determination of sample size using the width of confidence intervals and power. Correlation and regression: assumptions; method of least squares; interpretation; hypothesis testing; confidence and prediction intervals; residuals; regression diagnostics; transformations; collinearity; model selection; polynomial regression. Analysis of Variance models (one-way and two-way with equal numbers of observations per cell): model; assumptions; estimation and hypothesis testing; interaction and its interpretation; transformations; residuals; diagnostics. Design of experiments: randomisation; replication; blocking. Standard designs including completely randomised, randomised block and Latin square designs; factorial experiments: analysis; interpretation; introduction to confounding. Analysis of Covariance: detailed treatment of the case with one factor and one covariate; extension to more complex situations. Contingency tables: tests for association; odds ratios, including confidence intervals; introduction to loglinear models.

Assessment

Up to 50 pages of assignments and a 3 hour end-of semester written examination.