# STAT261 Probability and Inference 1

An introduction to probability theory and mathematical statistics. Probability, random variables, sampling distributions, estimation, hypothesis testing, simulation.

In the first year, Statistics papers emphasise the methods of statistics: which techniques and tests are applied in which situations. In this paper, you will learn some of the theory and mathematics behind those methods. This is important because you will:

• Better understand where those standard methods come from and why they are used
• Learn how to conduct analyses and design statistical methods for the many cases in which the 'standard' toolbox is inadequate
Modern statistics is a dynamic and rapidly changing subject. If you are going to keep up with the changes and advances in statistical theory and methodology, you will need a good grounding in mathematical statistics and probability theory.

Paper title Probability and Inference 1 STAT261 Statistics 0.1500 18 points First Semester \$868.95 \$3,656.70
Prerequisite
MATH 160 and one of STAT 110, STAT 115, COMO 101, BSNS 102, BSNS 112, QUAN 101
Schedule C
Arts and Music, Science
Eligibility
It is particularly useful for those majoring in Mathematics, Statistics, Economics, Finance and Quantitative Analysis, Psychology, Zoology or any other field in which statistics is used.
Contact
twang@maths.otago.ac.nz
Teaching staff
Dr Ting Wang and Dr Matthew Parry
Paper Structure
Main topics:
• Introduction to probability
• Random variables and distributions
• Expectation and variance
• Transformations of random variables
• Statistical models
• Estimators and likelihood
• Confidence intervals and hypothesis testing
• Bayesian inference
Teaching Arrangements
32 lectures and 10 tutorials.
Textbooks
Textbooks are not required for this paper.
Course outline
View course outline for STAT 261
Critical thinking, Information literacy, Self-motivation.
Learning Outcomes
Students who successfully complete the paper will develop an ability to conduct analyses and design statistical methods for cases in which the 'standard' toolbox is inadequate.

## Timetable

### First Semester

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

#### Lecture

Stream Days Times Weeks
Attend
L1 Tuesday 10:00-10:50 9-13, 15-22
Thursday 10:00-10:50 9-13, 15-22
AND
M1 Friday 10:00-10:50 9-12, 15-22

#### Tutorial

Stream Days Times Weeks
Attend one stream from
T1 Wednesday 15:00-15:50 10-13, 15-16, 18-22
T2 Wednesday 16:00-16:50 10-13, 15-16, 18-22