June 2014
|
Tuesday 24 |
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 statistical package SPSS will be used to illustrate the ideas demonstrated. The course will be held in a computer laboratory allowing participants to immediately apply the material covered through a series of practical examples.
|
|
July 2014
|
Tuesday 01 |
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.
|
Tuesday 08 |
9:00 - COURSE - ANOVA, Linear Regression and Logistic Regression : A Short Course using SPSS
|
Website |
More Information
|
The course is designed for people with knowledge of basic statistics who want to learn more about regression and analysis of variance (ANOVA).
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.
|
Monday 14 |
The course is designed as an applied course in Structural Equation Modelling (SEM) using the Mplus software package. SEM is used widely by researchers to test complex relationships among observed (measured) and latent (unobserved) variables and subsumes other analytical techniques such as regression, path analysis, factor analysis, and canonical correlation. Mplus is rapidly becoming the program of choice for the analysis of SEMs. 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. In addition, Mplus analyses multilevel modelling structures.
The first three days of the course will be an introduction to SEM and the Mplus program. The focus of the last two days of the course is on the analysis of more advanced SEM models.
If you are familiar with the Mplus program and have an understanding of material typically covered in an introduction to SEM course, you may choose to attend only the last two days of the course.
If you have completed an introductory course in SEM using another program (e.g., Amos, Lisrel, EQS) but have not previously used the Mplus program, you may choose to attend the first day and then the last two days of the course.
|
Wednesday 23 |
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.
|
|
September 2014
|
Tuesday 23 |
In this workshop, we will explore methods and models for forecasting time series. Topics to be covered include seasonality and trends, exponential smoothing, ARIMA modelling, dynamic regression and state space models, as well as forecast accuracy methods and forecast evaluation techniques such as cross-validation. The workshop will involve a mixture of lectures and practical sessions using R.
Workshop participants will be assumed to be familiar with basic statistical tools such as multiple regression and maximum likelihood estimation, but no knowledge of time series or forecasting will be assumed. Some prior experience in R is desirable.
UWA Postgraduate Research students receive subsidised fees.
|
Tuesday 30 |
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.
|
|
November 2014
|
Tuesday 11 |
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.
|
Tuesday 25 |
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 statistical package SPSS will be used to illustrate the ideas demonstrated. The course will be held in a computer laboratory allowing participants to immediately apply the material covered through a series of practical examples.
UWA Postgraduate students receive a subsidised rate.
|
|
November 2015
|
Thursday 19 |
16:00 - SEMINAR - Mathematics & Statistics Colloquium: Grrrrr...... linear stability should be simple -- the saga of the Stokes' layer
|
More Information
|
Mathematics & Statistics Colloquium
Time and date: 4pm, Thursday 19th November
Venue: Blakers Lecture Theatre
Speaker: Professor Andrew Bassom (The University of Western Australia)
Title: Grrrrr...... linear stability should be simple -- the saga of the Stokes' layer
Abstract: The linear stability of boundary layers is a subject which was thought to have been essentially solved
long ago. During my interview at UWA over 12 years ago I talked about some calculations directed towards
understanding the stability properties of a Stokes layer, which is the fluid flow set up when an oscillatory viscous flow
moves over a rigid boundary. Those computations gave results very different from experimental observations and
it is only relatively recently that we believe we have found a plausible explanation for the discrepancy. Here I shall
review a number of the various frustrations experienced in the research into this ostensibly straightforward problem (and
conclude that I should have given up long ago).
|
Monday 23 |
8:30 - COURSE - Introductory Analysis of Linked Health Data PUBH5785 : SPH Seasonal School 5 day 6 point unit
|
Website |
More Information
|
This unit aims to acquaint you with the theory and the practical skills needed for analysis of large sets of linked administrative health data at an introductory or intermediate level.
The School of Population Health offers a range of 5 day fulltime out of semester units for course credit or professional development at several points throughout the year. These are educational opportunities for a broad audience, allowing you to fit a whole semeester of teaching attendance into a week of classes.
For information on our units, including enrolment and fee information for this unit, simply visit seasonal school at sph.uwa.edu.au
Note that Advanced Analysis of Linked Health Data PUBH5802 is not being run in 2015, but will be offered again in December 2016.
|
|
December 2015
|
Tuesday 01 |
8:30 - Course - Multivariate Analysis : The course is intended as an introduction to some of the more commonly used multivariate statistical methods of data summary and analysis.
|
Website |
More Information
|
Topics will include Principal Component Analysis, Factor Analysis, Canonical Variate (or Canonical Correlation) Analysis, Discriminant Analysis, Cluster Analysis, Multidimensional Scaling and Ordination. Examples and exercises will be provided using the statistical package IBM SPSS, where possible. The course aims to provide an understanding of the ideas behind the analyses rather than be a mere button pressing exercise, although buttons will be pressed.
|
Wednesday 16 |
12:00 - TALK - Power/Sample Size Calculations : This seminar provides an overview of sample size calculations and demonstrates how to use the free "PS" software
|
More Information
|
Is it unethical to conduct studies that are too large or too small? If so, how do we find the right balance based on the available resources? This seminar provides an overview of sample size calculations and demonstrates how to use the free "PS" software to perform simple sample size calculations for the following study designs:
- Comparator studies (two sample t-test, paired t-test)
- Case-Control Studies (unmatched, matched)
- Cohort studies (test of 2 proportions or odds ratios)
- Survival Studies (log rank test)
It will conclude by reviewing potential sources for estimates of effect size or variability and identifying situations where the best course of action is to consult a statistician.
|
|
April 2016
|
Tuesday 19 |
8:30 - Short course - Introduction to statistics using Microsoft Excel : The course is open to anyone and is designed for those who have little or no experience with statistics or Microsoft Excel but who would like to learn more.
|
Website |
More Information
|
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.
|
|
July 2016
|
Tuesday 12 |
14:00 - Short course - ANOVA, Linear regression and Logistic Regression : The course is designed for people with knowledge of basic statistics who want to learn more about regression and analysis of variance (ANOVA).
|
Website |
More Information
|
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.
Although not essential, some basic familiarity with SPSS or similar statistical package would be beneficial. A brief introduction to SPSS can be emailed to you before the course by request.
The course will be held in a computer laboratory allowing participants to immediately apply the material covered through a series of practical examples.
For further information relating to fees, please see the following link: http://www.cas.maths.uwa.edu.au/courses/anova-regression
|
|
November 2016
|
Tuesday 15 |
8:30 - Course - Introductory Statistics : The course is open to anyone and is designed for people with little or no knowledge of statistics who want to develop understanding of basic statistics.
|
Website |
More Information
|
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 statistical package SPSS will be used to illustrate the ideas demonstrated. The course will be held in a computer laboratory allowing participants to immediately apply the material covered through a series of practical examples.
- $845 for all except UWA postgraduate research students (GST inclusive)
- $198 for UWA postgraduate research students (GST inclusive)
For further information, please see the following link: http://www.cas.maths.uwa.edu.au/courses/intro-stats
|
Tuesday 29 |
8:30 - Short Course - R Basics : This practical course introduces you to R, one of the most powerful tools for statistical computing.
|
Website |
More Information
|
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. Those without this experience are encouraged to attend the Introductory Statistics course first.
- $570 for all except UWA postgraduate research students (GST inclusive)
- $132 for UWA postgraduate research students (GST inclusive)
For further information, please see the following link: http://www.cas.maths.uwa.edu.au/courses/rbasics
|
|
February 2017
|
Tuesday 21 |
9:00 - COURSE - Statistics Short Course: Vector Generalized Linear and Additive Models : Vector Generalized Linear and Additive Models Course presented by Dr. Thomas Yee
|
Website |
More Information
|
The Vector Generalized Linear and Additive Models short course will be presented by Dr. Thomas Yee on 21-22 February 2017. Those attending the two-day course will receive a hard copy of Dr. Yee’s book "Vector Generalized Linear and Additive Models: With an Implementation in R”. Thomas W. Yee is a Senior Lecturer in the Department of Statistics at the University of Auckland, New Zealand. The author of over 30 articles published in statistical and other scientific journals, his work usually has a methodological focus and has direct applications in the fields of biostatistics and ecology. He is the author of the VGAM R package, one of the largest by a single author. Registrations and furthermore information can be found at http://www.cas.maths.uwa.edu.au/courses/vector-generalized-linear-and-additive-models. Please note that the early bird discount closes on 22 January 2017. If you have any questions or queries, please don't hesitate to contact the Centre for Applied Statistics at [email protected].
|
|
May 2017
|
Monday 01 |
18:00 - COURSE - R Basics Evening Course : This practical course introduces you to R
|
More Information
|
R is a free and extremely powerful language and software environment for statistical computing, data analysis, and graphics. This course is designed for those who have little to no experience with R, but have a basic understanding of statistics. Those without this knowledge are encouraged to attend the Introductory Statistics course first. More details at http://www.cas.maths.uwa.edu.au/courses/r-basics-evening-course
|
Tuesday 09 |
9:00 - EVENT - Statistics Short Course: Spatial Point Patterns : Analysis of spatial data using R and spatstat
|
Website |
More Information
|
Spatial point pattern datasets are becoming common across many fields of research. However, statistical methodology for analysing these data has not been easily accessible. This course is a practical introduction to the analysis of spatial point patterns with a strong focus on hands-on exercises throughout the course.
The course gives an in-depth introduction to spatstat, an R package for analysing spatial point patterns. The package supports a complete statistical analysis of spatial point pattern data: data input and inspection, calculations, plotting, exploratory data analysis, hypothesis tests, model-fitting, simulation, Monte Carlo methods and model diagnostics.
|
|
Alternative formats:
Default |
XML
|