What's On at UWA

The Annual Lecture is the highlight of the year for the UWA Historical Society and Convocation and we are delighted to welcome Winthrop Professor Cheryl Praeger to the podium to reflect upon her years on Campus and subsequent experiences and achievements.

Mathematician Cheryl Praeger has served the University of Western Australia as Lecturer, Senior Lecturer, and Professor since 1976. She leads a flourishing research group in pure mathematics and is in the top one per cent of highly cited mathematicians in the world.

Attendance is free.

The course is designed for people with knowledge of basic statistics who want to learn more about how to analyse binary or survival data.

The course is hosted by the Centre for Applied Statistics and we offer discounted rate fees to UWA Graduate Research Students.

Fee information is available on our website http://www.cas.maths.uwa.edu.au/courses. Please register online.

This course will take you through the basics you need to do statistical analyses in R, a powerful freeware statistical package.

The course will cover basic statistics such as t-tests, regression and ANOVA as well as producing high quality graphics.

The course is hosted by the Centre for Applied Statistics and we offer discounted rate fees to UWA Graduate Research Students.

Fee information is available on our website http://www.cas.maths.uwa.edu.au/courses. Please register online.

The course is designed for people with knowledge of basic statistics who want to learn more about designing and analysing experiments.

It will cover material ranging from a review of simple one-way ANOVA, to more complex designs and analyses including crossed and nested factors with fixed and random effects.

The course is hosted by the Centre for Applied Statistics and we offer discounted rate fees to UWA Graduate Research Students.

Fee information is available on our website http://www.cas.maths.uwa.edu.au/courses. Please register online.

SEM is used widely by researchers to test complex relationships among observed (measured) and latent (unobserved) variables. This course will introduce you to SEM and also covers issues relating to model specification, identification and estimation, assessing model fit (goodness-of-fit criteria), and dealing with problem data.

The course is hosted by the Centre for Applied Statistics and we offer discounted rate fees to UWA Graduate Research Students.

Fee information is available on our website http://www.cas.maths.uwa.edu.au/courses. Please register online.

The course is designed as a comprehensive coverage of applied SEM techniques using the Mplus statistical software package. Mplus offers a general modelling framework that allows both the modelling of cross-sectional and longitudinal data using observed variables that are a combination of continuous and categorical variables.

The course is hosted by the Centre for Applied Statistics and we offer discounted rate fees to UWA Graduate Research Students.

Fee information is available on our website http://www.cas.maths.uwa.edu.au/courses. Please register online.

The aim of this course is to introduce you to basic statistics. It will cover descriptive statistics (means and standard deviations); data exploration; basic categorical data analysis; simple linear regression and basic analysis of variance (ANOVA).

Subsidised rates are available for UWA Graduate Research Students.

Please register online.

Unfortunately this event has been cancelled.

Due to unforeseen circumstances the presenter is no longer available to deliver this course.

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This course aims to provide you with an introduction to the facilities available in MS Excel from a statistical point of view. As well as an introduction to Excel, spreadsheet functions and graphics, it concentrates on performing basic statistical methods, producing charts and tables, and discusses the limitations of Excel when it comes to more complex statistical analysis.

Discount fees are available to UWA Postgraduate Research Students.

Statistical meta-analysis deals with a variety of sophisticated statistical methods to efficiently combine the results of several studies that have a common target. In this course, we will describe the basic concepts of effect size for continuous measurements as well as qualitative attributes, combination of tests and estimates of effect size, tests for homogeneity of effect sizes, fixed versus random effects model of meta-analysis, combination of Gallup polls, meta-analysis of binary data, meta-regression, and publication bias.

The aim of this course is to introduce you to basic statistics. It will cover descriptive statistics (means and standard deviations); data exploration; basic categorical data analysis; simple linear regression and basic analysis of variance (ANOVA).

The course is subsidised for UWA postgraduate research students.

Our Epidemiology and Control of Communicable Diseases unit is designed to allow students to understand the principles of infectious disease emergence and transmission using current cases and examples.

The unit reviews the traditional tools of outbreak and epidemic investigation, combined with ideas on environmental change as a major driving force behind disease emergence.

Topics covered include:

- Australian and global perspectives on emerging and re-emerging infectious diseases - links between environmental change and infectious diseases - infections from food and water sources - vector-borne illnesses, with a major emphasis on Australian examples - principles of infectious disease transmission - infection patterns in at-risk populations - infectious disease surveillance - the assessment and management of epidemics and outbreaks - bioterrorism - successes and failures in infectious disease control

Unit outline

The five-day unit will consist of a combination of lectures, practical case studies and discussions of recent regional and global outbreaks. In preparation for the teaching week, pre-reading will be sent out in mid June.

Who should attend?

Anyone with an interest in infectious diseases, microbiology and/or environmental health issues is welcome. This includes microbiologists, health department staff, doctors, nurses, students of public health, researchers, managers, ecologists and environmental scientists, and anyone working in areas relating to infectious disease prevention and control.

This unit is available for postgraduate students as a 6 point unit. It is also available for professional development. Fees apply, please visit our website for details.

The course is designed for those who have no experience with R, but have a basic understanding of statistics. Those without this experience are encouraged to attend the Introductory Statistics course first.

This course covers material ranging from Kaplan Meier curves to the analysis of censored data and Cox's proportional hazards models.

Participants must bring their own laptop with R installed.

This course covers techniques that can be used to analyse data with continuous and categorical variables. The course will begin with simple linear regression and then proceed with approaches that can be used with more than two variables such as multiple regression. ANOVA with interactions and blocking will also be covered. The course will end with techniques that address the analysis of binary or ordinal variables.

Subsidised fees are available for UWA Graduate Research Students.

This course is aimed at anyone wishing to improve their survey questionnaires. This course is useful for both people new to questionnaire design and those who have experience and would like to extend their knowledge. It will be a benefit not only for people who anticipate designing a questionnaire in the future, but for those in the role of critiquing commissioned or existing research.

UWA Postgraduate Research students receive subsidised fees.

The Nurses’ Health Studies are among the largest and longest running investigations of factors that influence women’s health. Started in 1976 and expanded in 1989, the information provided by the 238,000 dedicated nurse-participants has led to many new insights on health and disease. While the prevention of cancer is still a primary focus, the study has also produced landmark data on cardiovascular disease, diabetes and many other conditions. Most importantly, these studies have shown that diet, physical activity and other lifestyle factors can powerfully promote better health.

R is a free and extremely powerful language and software environment for statistical computing, data analysis, and graphics. The course is designed for those who have no experience with R, but have a basic understanding of statistics. The course will include: Introduction to R: How to install R on your computer; basic R commands, how to use and understand the R help pages. Data: Reading in data and data manipulation; summarising data; basic statistical analysis and fitting linear models. Graphics and output: Basic plotting commands and how to customise your plots; how to export your plots and output in a user-friendly format. Functions: Writing simple functions and flow control structures.

Professor Tilling main areas of expertise are in methods for analysing exposures and outcomes across the life-course, and in methods for dealing with missing data. She has a mathematical background, an MSc in Applied Statistics and a PhD in Epidemiology, together with more than 15 years’ experience working in academic public health and epidemiology. Prof Tilling enjoys interpreting and explaining results from more complex statistical methods to other researchers and members of the public and using all forms of the media to effectively promote public health messages.

Areas of interest: Childhood growth; Life-course analyses; Trajectories of change in disease outcomes (E.g. PSA in prostate cancer, EDS in Multiple Sclerosis; Complex inter-relationships which change over time (E.g. fat mass and physical activity, risk factors for CHD; Methodological interests: Methods to examine and correct for bias due to missing data; Structural equation models, particularly for longitudinal data; Multilevel models for growth trajectories; Fractional polynomial and linear spline models Time-varying confounding - marginal structural models and g-estimation

The course will cover material ranging from a review of simple one-way ANOVA, to more complex designs and analyses including crossed and nested factors with fixed and random effects.The emphasis throughout will be placed on applications rather than theory. The statistical package R and R Commander will be used and some familiarity with this will be assumed.