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Data pervades almost every aspect of modern day life. But there are lots of ways in which this data can be abused. Our biases and preconceptions can lead us to make poor assumptions about the world, and there is no such thing as raw data - it needs to be cooked with care.
Data tells many stories - as long as you can learn to listen to it, and to ask the right questions of your data.
This course will take you a journey through a data set. You explore how correct your hidden assumptions are about a real dataset, and start to think about how that data might have been collected... you will explore the data, thinking about what types of variables it has, and how they are related to one another. Keep your mind open and your curiosity high!
You will need to think about what the patterns you uncover mean, whether they point to a real effect or are just a mistake, and how they might be correlated with other patterns in your data.
Finally, you will look at how data is used (and abused!) as evidence when people use it to tell stories.
This course is well suited to professionals wanting to learn about how to use data strategically to tell compelling stories.
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START DATE |
Start anytime |
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MODE |
Online |
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DURATION |
Self paced |
Kirsty’s research models the many ways in which humans interact with information, and how this can change as a result of context. She is working towards providing unified mathematical and computational models of contextuality, which often results in apparently complex and unpredictable human behaviour. She received an ARC Postdoctoral Fellowship for a Discovery Project investigating this problem. She has collaborated on projects with people from a wide range of fields, including Physics, Experimental Psychology, Cognitive Science, Computer Science, Social Psychology, Education and Computational Linguistics.
Simon’s broad background in educational research has led him a course focus on how people think about knowledge, and take action on that knowledge. In particular, he is engaged with the way people and policies implicate views on ‘knowledge’ in documents such as assessment policies. His teaching now focuses particularly on quantitative literacy, and teaching students to spot where statistical information has been used well, poorly, or omitted where it should not have been.
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