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Truth Seeker: How To Avoid Logical Fallacies And Cognitive Biases In Data Science

May 10, 2019 at 10:19 AM

We have released a new eBook titled Truth Seeker: a guide to avoiding logical fallacies and cognitive biases in data science.

The eBook introduces a host of important concepts where analytics and philosophy collide and includes various links to webpages to learn more about each concept. The eBook aims to help readers improve their metacognition (thinking about thinking), which will help you avoid common mistakes regularly made in data analytics. 

The author of the eBook, Thomas Maydon, is the Head of Credit Solutions at Principa. With over 16 years of experience in the Southern African, West African and Middle Eastern retail credit markets, Thomas has primarily been involved in consulting, analytics, credit bureau and predictive modelling services.

For some time, I have been interested in sceptical thinking and how we as humans commonly make logic flaws in our thinking. Philosophers have classified these flaws in a long list of informal logical fallacies and cognitive biases.” says Maydon.

As an analyst and mathematician, I was interested in how these errors in thinking permeate into the world of data science. It was clear that these same logical flaws exist in analytics.

The free eBook is available for download here.

Truthseeker - logical fallacies

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