[MINI] Bias Variance Tradeoff
Data Skeptic13 Nov 2015

[MINI] Bias Variance Tradeoff

A discussion of the expected number of cars at a stoplight frames today's discussion of the bias variance tradeoff. The central ideal of this concept relates to model complexity. A very simple model will likely generalize well from training to testing data, but will have a very high variance since it's simplicity can prevent it from capturing the relationship between the covariates and the output. As a model grows more and more complex, it may capture more of the underlying data but the risk that it overfits the training data and therefore does not generalize (is biased) increases. The tradeoff between minimizing variance and minimizing bias is an ongoing challenge for data scientists, and an important discussion for skeptics around how much we should trust models.

Episoder(588)

[MINI] p-values

[MINI] p-values

In 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.

13 Jun 201416min

Advertising Attribution with Nathan Janos

Advertising Attribution with Nathan Janos

A 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

[MINI] type i / type ii errors

In 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

Introduction

The 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.

23 Mai 20143min

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