Brought to you by QCIF in partnership with Griffith University Researcher Education and Development and delivered by Griffith University senior statistician A/Prof Sama Low-Choy, these three half-day workshops provide insight into a wide variety of statistical concepts and applications.
 
Places for these one-off workshops are very limited and only available to researchers from QCIF member institutions. Please use this form to apply for places at one or more of these workshops.

Session 1: Understanding probability

Tuesday 18th August, 1pm – 4pm. Online workshop.

This interactive tutorial will address a fundamental, subtle and often overlooked topic in statistics: the logic of probability. Understanding probability is an essential building block for anyone doing statistics in the 21st Century, in an age when we need to be conversant in multiple statistical paradigms. These include null hypothesis significance testing, classical or Frequentist statistical modelling, machine learning algorithms, and Bayesian statistical modelling.

Questions explored include: What is probability? What does it mean, exactly? What are common mis-interpretations and how can I avoid them? What is Bayes’ theorem, and why is understanding it important to differentiating between different statistical approaches?

We will use role-play to help you really think through what probabilities mean, and to become aware of and learn how to avoid common logical fallacies that can lead to misinterpretations of probabilities and misconceptions about what statistical analysis provides.

Relevant for any quantitive research project, this four hour introductory workshop requires nothing more than basic maths knowledge and a willingness to join in with group activities.

Session 2: Expanding your statistical universe: transitioning from hypothesis testing to statistical modelling

Tuesday 1st September, 10am – 2pm (including lunch break). Online workshop.

Pre-requisites: “Understanding Probability” workshop or equivalent background

Many researchers find themselves in the situation where they need to estimate a proportion of things – for instance of people, events, organizations, locations – that have something special about them. Examples of such a proportion might include: the percentage of people with an issue or needs regarding health, justice or education; or the proportion of locations suffering from environmental impacts, or where rare or pest species occur. 

Traditional statistics courses often introduce just a single approach of null hypothesis significance testing (NHST) that can be calculated “on the back of an envelope”: binomial test of proportions, or chi-squared tests. This has led to generations of researchers who are unaware of alternative statistical approaches that may be better suited to a particular applied problem, and means that inferences from NHST are often mis-interpreted.

In this seminar we walk you through the appropriate use, and practical ramifications, of using different statistical paradigms to approach a simple problem involving inference about a probability. We use an interactive exercise designed to engage multiple senses, to help through the rather abstract notions involved.

Session 3: What’s the difference? Classical vs Bayesian statistical modelling

Tuesday 8th September, 10am – 2pm (including lunch break). Online workshop.

Pre-requisites: “Expanding your statistical universe” workshop or equivalent background

This workshop helps newcomers to Bayesian analysis transition from their classical understanding of statistical modelling to a Bayesian one. Using regression to provide a simple and versatile context for enabling this transition, we explain the subtle differences in interpretation of model outputs.

Examples used will illustrate the impact of prior choices, from non-informative to informative, conjugate and otherwise. You will gain experience in how the prior can be harnessed to support a continually adaptive approach to updating your model as new information arrives. Code to reproduce examples will be provided in R.


Places at these workshops are available by application only, using this form. Please note, we expect demand to be high and may not be able to offer places to all applicants.