Who doesn’t love a good podcast?
Here’s a few of our Data team’s favourite podcasts about data and data analysis. Whether you’re interested in studying data analysis, or learning more about how data impacts our everyday lives, there’s a podcast for you.
BBC Radio 4’s More or Less: Tim Harford explains – and sometimes debunks – the numbers and statistics used in political debate, the news and everyday life. With subjects such as superforecasting, AI, and Netflix, this topical weekly podcast makes data compelling and hugely relevant to all our lives.
If you’re thinking about becoming a Data Scientist, there’s a podcast especially for you! Becoming a Data Scientist interviews with data scientists or someone on their way to becoming a data scientist, to learn about their path to get to where they are today. Some of the interviewees on this US-centric podcast include David Meza, the chief knowledge architect at NASA and Debbie Berebichez, a well-known physicist, TV host and STEM advocate.
This podcast isn’t just for women in STEM – on it you’ll hear all about the amazing achievements women are making in data. Leading women in data science share their work, advice, and the lessons they’ve learned along the way. Learn about how data science is being applied and has an impact across a wide range of industries, from healthcare to finance to cosmology to human rights and more.
Scotland’s innovation centre for data and AI has a series of conversations with some of the top members of the data science community, including Unicef, the NHS, Harvard Data Science Review and also our very own data team! The podcast is run by organisers of DataFest.
Roger Peng and Hilary Parker talk about the latest in data science and data analysis in academia and industry. Co-hosts: Roger Peng of the Johns Hopkins Bloomberg School of Public Health and Hilary Parker of Stitch Fix.
Interested in learning more about statistics? This podcast, run by Melbourne based James Fodor covers all things sciences, but in one episode he focuses on introducing key concepts of statistics, explained in as clear a manner as possible. It includes a discussion of key concepts of probability, types of statistical data, sampling methods, the difference between descriptive and inferential statistics, statistical significance, and p-values. He concludes with a brief look at three common statistical tests; the chi-square test, t-test, and linear regression.
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