The Statistical Consulting Centre in the National Institute of Applied Statistics Research Australia, School of Mathematics and Applied Statistics provides postgraduate students and staff members of the University of Wollongong with statistical consulting assistance for research.

Director: Professor Marijka Batterham

UOW SCHOLARS

Phone: +61 2 4221 8190
Email: marijka@uow.edu.au
Location: Building 39C Room 268

Consultant: Dr Brad Wakefield

UOW SCHOLARS

Emailbradleyw@uow.edu.au
Location: Building 39C Room 269

Aim

The service aims to improve the statistical content of research carried out by members of the University. Researchers from all disciplines may use the Centre. Priority is currently given to staff members and postgraduate students undertaking research for Doctor of Philosophy or Masters' degrees. The centre does not provide consulting support for honours students.

How we can help

It is important that University researchers consult the Centre at the beginning of their investigation, so that their research will include clear research hypotheses and well-designed data collection processes as these are basic to any analysis.

The assistance provided by the Statistical Consulting Centre includes advice on:

  • The planning of experiments,
  • Designing questionnaires,
  • Data collection,
  • Data entry and management,
  • Statistical analyses,
  • The presentation of results.

Planning the data gathering process is crucial to research, and consulting with the Statistical Consulting Centre at this stage will reap the most reward.

Currently the Statistical Consulting Centre provides each University researcher with a free initial consultation. Up to ten hours per calendar year of consulting time maybe provided without charge if research funding is not available. When researchers require more consulting time, or receive external funding, a service charge is necessary.

The Statistical Consulting Centre can arrange for later data entry and statistical analyses for those who wish to pay for these services rather than do the work themselves.

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Upcoming short courses

There are currently no events for this period

Short Courses Offered

 

Course description

“Meta-Analysis in a Month" is an introductory course aimed at researchers interested in learning how to apply meta-analysis in their research. Meta-analysis is a pivotal statistical technique that amalgamates results from multiple studies, offering a powerful tool for synthesising research findings and drawing more comprehensive conclusions.

The course is structured over three weeks, encompassing three detailed sessions:

Week 1: Data extraction for meta-analysis

  • Date: Tuesday 5th March 2024
  • Time: 1pm-5pm AEDT
  • Content:
    • Basics of meta-analysis.
    • Data extraction methods.
    • Introduction to statistical software (R).

Week 2: Performing a meta-analysis

  • Date: Tuesday 12th March 2024
  • Time: 1pm-5pm AEDT
  • Content:
    • Pooling data and assessing heterogeneity.
    • Running a meta-analysis with software.

Week 3: Advanced meta-analysis for publication

  • Date: Tuesday 19th March 2024
  • Time: 11am-5pm AEDT
  • Content:
    • Dealing with heterogeneity, missing data, multiple outcomes, and treatment arms.
    • Adjusting for publication bias.
    • Practical meta-analysis session and demonstration.

Learning outcomes

By the end of the course, participants will have gained:

  • A solid theoretical understanding of meta-analysis.
  • Hands-on experience in data extraction, analysis, and interpretation using statistical software.
  • Skills to prepare meta-analysis results for publication.

Instructors

Professor Marijka Batterham, Dr Brad Wakefield, and Rebecca Harris.

Requirements

The course requires usage of R and RStudio. Please ensure you have R and RStudio installed on your computer. Previous experience using R and RStudio is recommended.

Venue

Online streaming

Cost

$320 (or $300 via internal transfer) per participant.

Join Us

This course is ideal for those new to meta-analysis or those seeking to enhance their skills. With a focus on both theory and practical application, participants will be well-prepared to conduct and publish their own meta-analyses.

Spaces are limited – Register today to elevate your research skills!

To register please email Brad Wakefield - bradleyw@uow.edu.au with your name and details.

 

To effectively communicate research findings, researchers must possess the ability to create a diverse range of graphs and figures suitable for publication. In this workshop, you will learn the dos and don’ts of data visualisation, use either R or SPSS to create your visualisations, and choose the best visualisation for your data.

Target audience

Staff and postgraduate students who are interested in learning how to create a large range of customisable data visualisations. Note that previous experience with either SPSS or R is not required and all the required knowledge to create the visualisations will be contained in the workshop.

Course outline

In this workshop, you will learn the dos and don’ts of data visualisation use either R and RStudio or SPSS to create your visualisations and choose the best visualisation for your data.

We will cover a range of chart types, demonstrating how to visualise:

  • amounts
  • proportions
  • distributions
  • estimates
  • uncertainty
  • trends
  • time-dependent
  • and geographical data.

By the end of the workshop, you will have gained a solid understanding of the principles of good data visualisation and the necessary skills to create effective visualisations in either SPSS with Chart Builder or R with ggplot2.

Instructors

Dr Brad Wakefield and Professor Marijka Batterham, National Institute of Applied Statistics Research Australia.

Date and Time

The course will be from 9.30 am - 12.30 pm, and split over two days:

Monday, 16 October 2023

Tuesday, 17 October 2023

Venue

Online via Zoom - Link will be sent out before the workshop.

Cost

$110 or $100 from internal account.

 

For more information on the course please contact Brad Wakefield - bradleyw@uow.edu.au.

For enrolment information contact Karin Karr - karink@uow.edu.au.

 

REGISTER NOW

R is a widely used free statistical programming language. This workshop provides an introduction to R and its use through RStudio. The workshop covers data manipulation, visualisation and analysis. 

Target audience

Postgraduate students and staff who have previously completed an introductory statistics or data analysis subject and are planning to collect and manipulate, visualise and/or analyse data using R/RStudio.

Course outline

The course includes:

  • Data manipulation
    • Importing data
    • Defining variables
    • Computing new variables
    • Saving data and output
  • Visualisation
  • Inference/modelling
    • Proportions
    • Crosstabulations
    • T-tests
    • ANOVA
    • Correlation
    • Linear regression  

Please be aware that this workshop teaches the computing not statistics, it is assumed you have previous knowledge of basic statistics for the modelling session.

Instructors

Dr Brad Wakefield and Professor Marijka Batterham, National Institute of Applied Statistics Research Australia. 

For more information on the course please contact Brad Wakefield - bradleyw@uow.edu.au.

For enrolment information contact Karin Karr - karink@uow.edu.au.

Cost

$110 or $100 from internal account.

NOTE

You must install R and RStudio prior to the course. They are both FREE and instructions will be provided in advance. This course runs in both online and in-person options.

This one-day workshop provides an introduction to SPSS. The workshop covers data manipulation, visualisation, and analysis.

Target audience

Postgraduate students and staff who have previously completed an introductory statistics or data analysis subject and are planning to collect and manipulate, visualise and/or analyse data using SPSS.

Course outline

The course includes:

  • Data manipulation
    • Importing data
    • Defining variables
    • Computing new variables
    • Saving data and output
  • Visualisation
  • Inference/modelling
    • Crosstabulations
    • T-tests
    • Correlation
    • Linear regression  

Please be aware that this workshop teaches computing not statistics. It is assumed you have previous knowledge of basic statistics for the modelling session.

 

Instructors

Dr Brad Wakefield and Professor Marijka Batterham, National Institute of Applied Statistics Research Australia. 

For more information on the course please contact Brad Wakefield - bradleyw@uow.edu.au.

For enrolment information contact Karin Karr - karink@uow.edu.au.

Cost

$110 or $100 from internal account.

NOTE

This is a face-to-face workshop with no online option.

Jamovi is an easy-to-use FREE menu driven statistical package that integrates with R. Jamovi is an ideal introductory data analysis package. This one day workshop provides an introduction to Jamovi and how to perform data manipulation, visualisation and analysis. 

Target audience

postgraduate students/staff who have previously completed an introductory statistics or data analysis subject and are planning to collect and manipulate, visualise and/or analyse data. 

Course outline

The course includes:

  • Data manipulation
    • importing data
    • defining variables
    • computing new variables
    • saving data and output
  • Visualisation
  • Inference/modelling
    • proportions
    • crosstabulations
    • correlation
    • linear regression  

Please be aware that this workshop teaches the computing not statistics, it is assumed you have previous knowledge of basic statistics for the modelling session.

Instructor

Brad Wakefield and Professor Marijka Batterham, National Institute of Applied Statistics Research Australia. 

For more information on the course please contact Marijka Batterham marijka@uow.edu.au or Brad Wakefield bradleyw@uow.edu.au.

This is a face to face workshop, if you are requiring an online option or the course is full and you wish to be placed on a waiting list, please contact karink@uow.edu.au, an online version will be conducted at a later time if there is the demand.

Time

TBD

Venue

TBD

Cost

A charge of $110 (or $100 from an internal account).

NOTE

You must bring your own laptop to the course with Jamovi installed. Instructions will be provided prior to the course.

This is a unique entry level workshop specifically designed to teach the basics of data science and machine learning for the health and social sciences.

Course outline

The workshop will cover the most in demand data science and machine learning methods for both supervised (regression, classification and regression trees, neural nets and support vector machines) and unsupervised learning (clustering). Participants will learn how to choose the appropriate method, and how to analyse and interpret the results using RStudio. No prior knowledge of RStudio is necessary, RStudio will be introduced as part of the course. 

Instructor

Professor Marijka Batterham, Professor Alberto Nettel-Aguirre, and Dr Brad Wakefield from the Statistical Consulting Centre and the Centre for Health and Social Analytics 

Dates

TBD

Time

TBD

Introductory cost

TBD

Contact: marijka@uow.edu.au for additional course information

Course outline

Mixed modelling is central to modern statistical analysis and is often considered the go-to analysis for large health, social science, ecological, and biological data sets, particularly when there are repeated measurements for each subject or when there is clustering or multiple-levels apparent in the data. Mixed models can also be applied to longitudinal data with missing observations, a common hinderance to fitting ANOVA models. Able to be used across many data situations, mixed models are a form of regression analysis that are essential for any pioneering data analyst to have available to them.

This introductory in-person workshop covers the basics of building linear statistical models, covering standard regression analysis, interpreting categorical predictors and using interaction terms. We introduce exactly what are mixed models, what data is suited to mixed models, how to apply mixed models in R, and how to properly interpret the results. We will also cover the basics of using R and RStudio and give an overview of the tidyverse functions that can help get your data in the correct form for analysis. No prior knowledge of R is necessary. We will also show you how to create appealing data visualisations for clustered data using ggplot2.

Register