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Unit Overview

Description

Statistical methods are used to analyse data in a wide variety of fields (e.g. engineering, medicine, agriculture, business, economics, psychology, genetics, criminology, the social sciences). Such real world data often present challenges to data scientist and data analysts. For example, some of the data may be missing, some observations may be inconsistent with the rest of the data, the standard assumptions (e.g. normality) may fail, and the standard methods may not answer the important questions. While statistical theory can be helpful in analysing such data, its direct application may be limited by these practical problems. The best way to learn how to deal with these practical problems is to gain experience in analysing real data. This unit provides this experience by applying various statistical methods, through case studies and projects, to interesting practical problems rather than concentrating on the theory behind the methods.

The unit covers applications of a number of widely used statistical techniques selected from advanced regression topics (for example generalised linear models or nonlinear regression models), survival analysis, non-parametric statistics, multivariate analysis, and time series analysis. Furthermore, throughout the unit a large emphasis is placed on data visualisation techniques.

Credit
6 points
Offering
AvailabilityLocationMode
Not available in 2025UWA (Perth)Face to face
Outcomes

Students are able to (1) produce appropriate high quality data visualisations using a variety of software packages and techniques; (2) apply statistical reasoning to analyse the essential structure of problems in various fields of darta science; (3) extend their knowledge of statistical modelling techniques and adapt known solutions to different situations; and (4) interpret and communicate results of a statistical analysis in a logical and coherent fashion.

Assessment

Indicative assessments in this unit are as follows: (1) assignments; (2) tests; and (3) a final examination. Further information is available in the unit outline.



Student may be offered supplementary assessment in this unit if they meet the eligibility criteria.

Unit Coordinator(s)
Professor Inge Koch
Unit rules
Prerequisites
STAT2401 Analysis of Experiments
and STAT2402 Analysis of Observations
or STAT2062 Fundamentals of Probability with Applications
Incompatibility
STAT3064 Statistical Learning
and STAT5061 Statistical Data Science
Contact hours
Lectures: 3-hours per week
Labs 1-hour per week
Note
STAT4067 will be replaced by STAT5061 Statistical Data Science from 2022.
  • The availability of units in Semester 1, 2, etc. was correct at the time of publication but may be subject to change.
  • All students are responsible for identifying when they need assistance to improve their academic learning, research, English language and numeracy skills; seeking out the services and resources available to help them; and applying what they learn. Students are encouraged to register for free online support through GETSmart; to help themselves to the extensive range of resources on UWA's STUDYSmarter website; and to participate in WRITESmart and (ma+hs)Smart drop-ins and workshops.
  • Visit the Essential Textbooks website to see if any textbooks are required for this Unit. The website is updated regularly so content may change. Students are recommended to purchase Essential Textbooks, but a limited number of copies of all Essential Textbooks are held in the Library in print, and as an ebook where possible. Recommended readings for the unit can be accessed in Unit Readings directly through the Learning Management System (LMS).
  • Contact hours provide an indication of the type and extent of in-class activities this unit may contain. The total amount of student work (including contact hours, assessment time, and self-study) will approximate 150 hours per 6 credit points.