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# STAT30280

#### Inference for Data Analytics (online) (STAT30280)

Subject:
Statistics & Actuarial Science
College:
Science
School:
Mathematics & Statistics
Level:
3 (Degree)
Credits:
5
Module Coordinator:
Dr Michael Salter-Townshend
Trimester:
Spring
Mode of Delivery:
Online
Internship Module:
No

Curricular information is subject to change.

Purposes of statistical inference and learning from data. What is learnt, how it is done and why. Theory covering probability, random variables, likelihoods. Algorithms for performing inference, including implementation using software. Comparison of methods and how to critically assess them.

###### Learning Outcomes:

By the end of the course, students should be able to:
- identify which distribution is appropriate for certain types of data
- understand the purposes of inference and how to do it in practice
- estimate parameters and their associated uncertainty via likelihood methods, and interpret these values in the context of real-world problems.
- incorporate prior information into common statistical problems and obtain posterior probability distributions of parameters of interest.

###### Indicative Module Content:

Background of what is inference, recap on probability theory, random variables, common distributions for data.
Random vectors, independence, and conditional distributions.
Expectation, covariance, correlation.
Properties of random samples and asymptotics.
Frequentist statistical inference (method of moments, MLE, confidence intervals).
Uncertainty of estimates: parametric and non-parametric.
Numerical inferential algorithms.
Hypothesis testing.
Introduction to Bayesian inference.
Decision theory.

###### Student Effort Hours:
Student Effort Type Hours
Specified Learning Activities

24

Autonomous Student Learning

70

Online Learning

24

Total

118

###### Approaches to Teaching and Learning:
Requirements, Exclusions and Recommendations
Learning Requirements:

Calculus: familiarity with differentiation and integration. Students are required to have completed an introductory statistics module such as STAT10060 or STAT40720.

Module Requisites and Incompatibles
Incompatibles:
STAT20100 - Inferential Statistics

Assessment Strategy
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered

Not yet recorded.

Carry forward of passed components
No

Resit In Terminal Exam
Summer Yes - 2 Hour