Overview
Learn how data analytics affects everyone with the University of Adelaide
In an increasingly data-centric world, a working understanding of data analytics and quantitative methods is essential for all members of society.
This six-week course will teach you fundamental quantitative methods for dealing with data. Armed with this knowledge, you’ll be able to interpret and critically evaluate claims you encounter in your day-to-day life.
Through case studies, you’ll explore the foundational concepts in data science and statistical thinking. You’ll also discover machine learning and data science methods, and understand both the possibilities and pitfalls of these emerging sciences.
Learn how to identify misleading statistics
When presented with claims in the media that are accompanied by statistics, diagrams, and outputs from technologies like AI and machine learning, how can we learn to not be fooled by these claims?
This course will help you understand misleading statistics and learn how to challenge them when they are presented to you.
Delve into sample, variability, and study design
Next, you’ll explore the different components of research including research questions, sampling, and variability.
Using case studies, you’ll explore how sampling can go wrong as you learn the best practices. You’ll then move on to study design to understand the types of studies you may encounter.
Unpack the rules for analysing data
On the final weeks of the course, you’ll explore how bias can infiltrate surveys. You’ll also discover basic rules for analysing data to ensure a fair result is achieved.
Armed with this knowledge, you’ll have the confidence to accurately read and interpret the data you are presented with in everyday life.
This course is designed for anyone interested in critically interpreting data and developing their data literacy skills.
It will be particularly useful for those who interact with data in their current role.
Syllabus
- Misleading statistics
- Getting started
- Introduction to Week 1
- Misleading statistics
- How to fool the world with percentages
- Fermi estimation
- Statistics in the media
- Bringing it all together
- Sampling and variability
- Introduction to Week 2
- Hempel’s Paradox
- Sampling
- Variability
- Sample size and variability
- Assessment
- Bringing it all together
- Study design
- Introduction to Week 3
- Generalisability
- Types of studies
- Bringing it all together
- Surveys and bias
- Introduction to Week 4
- Surveys and bias
- Leading questions
- Bias and precision
- Assessment
- Bringing it all together
- Analysing results
- Introduction to Week 5
- What type of data is it?
- Rules for surveys
- Right censoring
- Bringing it all together
- Sampling gone wrong
- Introduction to Week 6
- Missing data
- The Tinder Example
- Experiment design
- Over-extrapolation
- Filter bubbles
- Wald’s Planes
- Assessment
- Bringing it all together
- What’s next?