Courses Handbook 2007 - [ Archived ]

307591 (v.2) Statistical Data Analysis 103

Area:

 Department of Mathematics and Statistics

Credits:

 12.5

Contact Hours:

 3.0
 
** The tuition pattern below provides details of the types of classes and their duration. This is to be used as a guide only. For more precise information please check your unit outline. **
 

Lecture:

 1 x 2 Hours Weekly

Tutorial:

 1 x 1 Hours Weekly

Prerequisite(s):

 307590 (v.2) Statistical Data Analysis 101
AND
310532 (v.1) Statistical Data Analysis 102 or any previous version
 

Syllabus:

 Regression analysis - simple linear regression, measures of model adequacy, residual analysis, transformations, inference for slope and intercept, confidence and prediction intervals for future responses. Multiple linear regression analysis - estimation of model parameters, inference regarding model parameters and predictions, analysis of variance, regression diagnostics, variable selection and model building. Non-parametric methods - sign test, signed-rank test, rand-sum test, runs test. Kruskal Wallacetest, rank correlation coefficient checking distributions - Q-Q plots and Kilmogorov Smirnov Test.
 
** To ensure that the most up-to-date information about unit references, texts and outcomes appears, they will be provided in your unit outline prior to commencement. **
 

Field of Education:

 010101 Mathematics

Funding Cluster:

 04 - Mathematics, Statistics

SOLT (Online) Definitions*:

 Essential
*Extent to which this unit or thesis utilises online information

Result Type:

 Grade/Mark

Availability
Availability Information has not been provided by the respective School or Area. Prospective students should contact the School or Area listed above for further information.

 
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