The Statistical Consulting Centre presents a free monthly seminar series on topics of interest to analysts and researchers including graduate students.
The seminars will cover a wide range of topics, with a practical and applied focus. Each presentation will run for around 30 minutes, allowing plenty of time for questions. The seminars are run online on the second Friday of each month via Zoom, starting at 12:30pm.
Get updates about the SCC seminar series
The multiple testing problem: how important is it and what can you do about it?
12:30 pm Friday 12th June 2026
Dr Sandy Clarke-Errey
It is generally true that the more hypothesis tests you perform, the greater the probability that one of those tests is statistically significant by chance, the so-called multiple testing problem. At the Statistical Consulting Centre, we regularly receive enquiries regarding this issue. Reviewers often ask for adjustment for multiple comparisons. But how important is it? What can you do about it?
Dr Sandy Clarke-Errey wrote her PhD on the performance of multiple hypothesis testing procedures in the presence of dependence in the high dimensional setting. She has an ongoing theoretical interest in the methods used, but a much stronger practical interest in helping people understand the issues surrounding their use and interpretation.
This seminar will outline some principles to consider, along with practical advice.
What is a mixed model and why should I use it?
12:30 pm Friday 10th July 2026
Cameron Patrick
Data with a hierarchical structure is very common in many fields. Terms used to describe this kind of data include multi-level data, longitudinal data, split-plot designs or repeated measures designs. These terms arose from different contexts, but they share a common feature. Observations are not independent, and there is structure to the dependence which can be incorporated into a statistical model.
Linear mixed-effects models ("mixed models") are a commonly used statistical method for multi-level or longitudinal data. Mixed models are versatile, capable of accounting for complex hierarchical structures, missing outcome data, and outcome variables with different distributions.
Cameron Patrick has worked with and supported many clients across a broad range of applications who need to use mixed models in their analysis. In this seminar, Cam will discuss the need for, and the practical application of, mixed models. Examples will be drawn from different fields of study.
Missed a squiggle? Moving beyond linear models
12:30 pm Friday 14 August 2026
Linear models are the foundation for most classical methods in statistics; they are simple, powerful and readily interpretable. However, the linearity assumption does not always hold, and it can be useful to know how to relax this assumption. You can come to the wrong conclusion if you have "missed a squiggle" without knowing it! We will explore generalised linear models as a means of testing the linearity assumption and adapting the model using patterns in the data themselves. We will discuss how you can get the most out of such models, and the trade-offs involved in moving away from the well-worn path of linear models.
Upcoming seminars
- Getting started with meta-analysis
- Applications of tree-based models
- Survival analysis
Missed a seminar? We can present to your group
If you would like us to present one of the seminars listed below to your lab or research group, contact Professor Ian Gordon.
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12:30pm Friday 8th May 2026
Associate Professor Sue Finch
Researchers have access to a wide range of statistical software, but it can sometimes be challenging to decide which is the best choice to suit particular needs. This seminar will showcase some popular statistical software - R, SPSS and Minitab. We will discuss the considerations that can guide the choice of software based on individual preferences, needs and longer term goals.
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12:30pm Friday 10th April 2026
Associate Professor Graham Hepworth
“You can’t fix by analysis what you bungled by design.” (Light, Singer and Willett, 1990)
Good study design in one of the foundations of meaningful empirical research. In this seminar, we discuss the principles of good experimental design. These principles are important for anyone contemplating running an experiment.
Associate Professor Graham Hepworth will share his vast experience in experimental design in around 40 years of consulting with researchers in agriculture, medicine and allied sciences, and many other disciplines. He will highlight examples of the best and worst in experimental design.
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12:30pm Friday 13th March 2026, Professor Ian Gordon
You’re a researcher at the University of Melbourne. Or a member of an analytics team in the finance industry. Or a market researcher.
Do you need help from statistics, or data science? Or something else again?
In this seminar I discuss these terms, and how you can navigate your way through the sometimes bewildering array of concepts and activities that aim to support or collaborate with anyone pursuing quantitative inquiry.