302316 (v.1) Statistical Inference 301


Area:

Department of Mathematics and Statistics

Credits:

25.0

Contact Hours:

4.0
 
** 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:

3 x 1 Hours Weekly

Tutorial:

1 x 1 Hours Weekly

Prerequisite(s):

302315 (v.2) Mathematical Statistics 202 or any previous version
 

Syllabus:

Procedures and properties of estimators - Fisher information, Cramer-Rao bound, consistency, sufficiency and Rao-Blackwell theorem. Hypothesis testing - Neyman-Pearson Lemma likelihood ratio, power function and confidence sets. Bayesian inference and nexus with likelihood. Monte Carlo, Boot-Strap and resampling Methods. Review of matrix algebra-random vectors, mean vectors and covariance matrices. Multivariate normal and its associated distributions.
 
** 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:

10100 Mathematical Sciences (Narrow Grouping)

HECS Band (if applicable):

2

Extent to which this unit or thesis
utilises online information:

Not Online

Result Type:

Grade/Mark

Availability

Year Location Period Internal Area External Central External
2004 Bentley Campus Semester 1 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