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.
Statistical Consulting Centre
Director: Professor Marijka Batterham
Phone: +61 2 4221 8190
Email: marijka_batterham@uow.edu.au
Location: Building 39C Room 268
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.
Short Courses Offered
- Introduction to R and RStudio workshop
- Meta-Analysis in a Month
- How to Create Graphs and Figures for Publication
- Introduction to IBM® SPSS® Statistics workshop
- Introduction to Jamovi workshop
- Introduction to Data Science & Machine Learning for Health and Social Sciences workshop
- Introduction to Mixed Modelling
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.
Date and Time
10:00am – 4:00pm, Tuesday 14 May 2024
Venue
Building 39c.174 and Online
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.
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.
This one-day workshop provides an introduction to SPSS. The workshop covers data manipulation, visualisation, and analysis.
Target audience
Postgraduate students and staff with introductory knowledge of statistics or data analysis.
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 ($100 when paid via internal transfer)
Date and Time
10:30 AM - 4:00 PM, 4th September 2024
Venue
On-Campus (Wollongong), Building 17-109
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.
Target Audience
Postgraduate students and staff with introductory knowledge of statistics or data analysis.
Date and Time
10:00 AM – 4:30 PM, 10th September 2024
Format
Online
Cost
$110 ($100 when paid via internal transfer)