Principal speaker
Adjunct Professor Sama Low-Choy
Other speakers
Dr Daniela Vasco
This interactive tutorial will redress a fundamental, subtle and often overlooked, topic in statistics: the logic of probability. Questions explored include:
What is probability?
What does it mean, exactly?
What are common mis-interpretations and how can I avoid them?
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 several statistical paradigms. This includes 1930s-style methods of null hypothesis significance testing, for confirmatory analyses, and to be able to read historical research. It also includes mid-20th century methods of classical or Frequentist statistical modelling, e.g. involving maximum likelihood estimation, asymptotic standard errors. Probability is key to understanding and making the most of Bayesian statistical methods, updating current knowledge (expressed as non-informative or informative priors) to posteriors. Though not often acknowledged probability still underpins 21st century methods of machine learning algorithms, for analysis of big data, which surprisingly often have a statistical modelling analogue. Understanding probability can enhance the simplest quant research, even in mixed (qual and quant) contexts.
We will use role-play to help you really think and talk through what probabilities mean, in the context of an environmental dilemma. Through seeking to understand and contributed to dialogues around the trial, activities aim to help you become aware of common logical fallacies. Recognizing these unfortunate misinterpretations of probabilities, may help you avoid misconceptions about what statistical analyses can provide and what they mean.
Format: Role-play - a mock trial, involving interaction in a large group, and discussion in small groups
Duration: 4 hours (including a break)
Prerequisite: Basic arithmetic: addition, subtraction, multiplication, fractions
Connections: Excellent foundation concepts for any statistical or data science course
Intended audience: All levels welcome.
Event categories
RSVP
RSVP on or before Tuesday 23 May 2023 20.33 pm, by email red@griffith.edu.au , or via https://events.griffith.edu.au/d/n0qns3/