School of Mathematics and StatisticsHome | About the school | Contact | Courses | Research | Personnel list
MT4606 STATISTICAL INFERENCE
Aims- To show how the methods of estimation and hypothesis testing met in MT2004 and MT3606 can be justified and derived.
- To extend those methods to a wider variety of situations.
- To show how different point estimators can be compared.
ObjectivesBy the end of the course students are expected to
- be familiar with the distributions listed in the syllabus.
- identify sufficient statistics and appreciate why they are important.
- derive bounds on variances provided by the Cramér-Rao inequality.
- derive maximum likelihood estimators of one and two dimensional parameters and establish their major properties.
- appreciate the relationship between frequentist confidence sets and tests of hypotheses.
- Distribution theory: Multinomial and negative binomial distributions.
- Point estimation: Mean square error. Unbiasedness.
- Hypothesis testing: Neyman-Pearson lemma. Uniformly most powerful tests. Likelihood ratio tests.
- Confidence sets: Pivotal quantities.
TextbooksIntroduction to the Theory of statistics: A M Mood, F A Graybill & D C Boes, McGraw Hill;
Probability and Statistics: M H DeGroot, Addison-Wesley;
Statistical Inference: G Casella & R L Berger, Brooks/Cole;
Statistical Inference: S D Silvey, Chapman & Hall;
Statistical Theory: B W Lindgren, Collier MacMillan.
Assessment2 Hour Examination = 100%
AvailabilityAcademic year 2013/14 in semester 2 at 12
LecturerDr I B J Goudie
Click here to see the University Course Catalogue entry.
Revised: PMH (April 2012)