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STAT370 Statistical Inference

A continuation of the theoretical development begun in STAT 270, this paper will cover the theory of ordinary least squares, maximum likelihood estimation and inference, hypothesis testing, and Bayesian inference.

Paper title Statistical Inference
Paper code STAT370
Subject Statistics
EFTS 0.1500
Points 18 points
Teaching period Second Semester
Domestic Tuition Fees (NZD) $886.35
International Tuition Fees (NZD) $3,766.35

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Prerequisite
(STAT 270 or STAT 261) and MATH 170
Restriction
STAT 362
Schedule C
Arts and Music, Science
Contact

katrina.sharples@otago.ac.nz

Teaching staff

Dr Matthew Parry

Textbooks

Textbooks are not required for this paper.

Useful references:

  • Mathematical Statistics with Applications by Wackerly, Mendenhall and Scheaffer
  • An Introduction to Mathematical Statistics and its Applications by Larsen and Marx

A full set of lecture notes is available on the Departmental website.

Graduate Attributes Emphasised
Communication, Critical thinking, Information literacy.
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.

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Timetable

Second Semester

Location
Dunedin
Teaching method
This paper is taught On Campus
Learning management system
Other

Lecture

Stream Days Times Weeks
Attend
A1 Tuesday 11:00-11:50 28-34, 36-41
Wednesday 11:00-11:50 28-34, 36-41
Friday 11:00-11:50 28-34, 36-41

Tutorial

Stream Days Times Weeks
Attend
A1 Wednesday 15:00-15:50 28-34, 36-41

A continuation of the theoretical development begun in STAT 270, 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
Paper code STAT370
Subject Statistics
EFTS 0.1500
Points 18 points
Teaching period Second Semester
Domestic Tuition Fees Tuition Fees for 2020 have not yet been set
International Tuition Fees Tuition Fees for international students are elsewhere on this website.

^ Top of page

Prerequisite
(STAT 270 or STAT 261) and MATH 170
Restriction
STAT 362
Schedule C
Arts and Music, Science
Eligibility

Students should have completed both STAT 270 (or 261) and MATH 170

Contact

Dr Ting Wang

Teaching staff

To be confirmed

Paper Structure

Main topics

  • 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

Textbooks are not required for this paper

Graduate Attributes Emphasised
Lifelong learning, Scholarship, Critical thinking, Information literacy, Research, Self-motivation.
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.

^ Top of page

Timetable

Second Semester

Location
Dunedin
Teaching method
This paper is taught On Campus
Learning management system
Other

Lecture

Stream Days Times Weeks
Attend
A1 Tuesday 11:00-11:50 28-34, 36-41
Wednesday 11:00-11:50 28-34, 36-41
Friday 11:00-11:50 28-34, 36-41

Tutorial

Stream Days Times Weeks
Attend
A1 Wednesday 15:00-15:50 28-34, 36-41