|
| |
302316 (v.1) Statistical Inference 301
Area: | Department of Mathematics and Statistics |
Contact Hours: | 4.0 |
Credits: | 25.0 |
Lecture: | 3 x 1 Hours Weekly |
Tutorial: | 1 x 1 Hours Weekly |
Prerequisite(s): | 302315 (v.2) Mathematical Statistics 202 or any previous version
|
| 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. |
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 |
|
Click here for a printable version of this page
|
|
|
|
