A continuation of the theoretical development begun in STAT270, this paper will cover the theory of ordinary least squares, maximum likelihood estimation and inference, hypothesis testing, and Bayesian inference.
This course continues to develop theory for making inference from data that was introduced in STAT 270 (or STAT 261). The tools developed by statisticians for analysing data have become a major factor in the advancement of scientific knowledge. Why are these tools so useful? The reason is that they are based on an agreed system of mathematical and statistical reasoning. In order to be confident that the methods used by a statistician are reliable we need an understanding of this theory.
|Paper title||Statistical Inference|
|Teaching period||Semester 2 (On campus)|
|Domestic Tuition Fees (NZD)||$955.05|
|International Tuition Fees||Tuition Fees for international students are elsewhere on this website.|
- MATH 140 and (STAT 261 or STAT 270)
- STAT 362
- Schedule C
- Arts and Music, Science
Students should have completed both STAT270 (or STAT261) and MATH140 (or MATH170).
- Teaching staff
Associate Professor Ting Wang
Dr Austina Clark
Associate Professor Matthew Schofield
- Paper Structure
- The general linear model
- The likelihood function
- Bayesian inference
- Maximum likelihood estimation
- Hypothesis testing using the likelihood function
- Model selection using the likelihood function
Textbooks are not required for this paper
- Graduate Attributes Emphasised
- Lifelong learning, Scholarship, Critical thinking, Information literacy, Research,
View more information about Otago's graduate attributes.
- Learning Outcomes
Students who successfully complete the paper will develop an understanding of key concepts in mathematical statistics.