Synopsis
Data Skeptic is a data science podcast exploring machine learning, statistics, artificial intelligence, and other data topics through short tutorials and interviews with domain experts.
Episodes
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[MINI] p-values
13/06/2014 Duration: 16minIn this mini, we discuss p-values and their use in hypothesis testing, in the context of an hypothetical experiment on plant flowering, and end with a reference to the Particle Fever documentary and how statistical significance played a role.
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Advertising Attribution with Nathan Janos
06/06/2014 Duration: 01h16minA conversation with Convertro's Nathan Janos about methodologies used to help advertisers understand the affect each of their marketing efforts (print, SEM, display, skywriting, etc.) contributes to their overall return.
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[MINI] type i / type ii errors
30/05/2014 Duration: 11minIn this first mini-episode of the Data Skeptic Podcast, we define and discuss type i and type ii errors (a.k.a. false positives and false negatives).
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Introduction
23/05/2014 Duration: 03minThe Data Skeptic Podcast features conversations with topics related to data science, statistics, machine learning, artificial intelligence and the like, all from the perspective of applying critical thinking and the scientific method to evaluate the veracity of claims and efficacy of approaches. This first episode is a short discussion about what this podcast is all about.