False Discovery Rates
Data Skeptic28 Sep 2018

False Discovery Rates

A false discovery rate (FDR) is a methodology that can be useful when struggling with the problem of multiple comparisons.

In any experiment, if the experimenter checks more than one dependent variable, then they are making multiple comparisons. Naturally, if you make enough comparisons, you will eventually find some correlation.

Classically, people applied the Bonferroni Correction. In essence, this procedure dictates that you should lower your p-value (raise your standard of evidence) by a specific amount depending on the number of variables you're considering. While effective, this methodology is strict about preventing false positives (type i errors). You aren't likely to find evidence for a hypothesis that is actually false using Bonferroni. However, your exuberance to avoid type i errors may have introduced some type ii errors. There could be some hypotheses that are actually true, which you did not notice.

This episode covers an alternative known as false discovery rates. The essence of this method is to make more specific adjustments to your expectation of what p-value is sufficient evidence.

Denne episoden er hentet fra en åpen RSS-feed og er ikke publisert av Podme. Den kan derfor inneholde annonser.

Episoder(601)

Streetlight Outage and Crime Rate Analysis with Zach Seeskin

Streetlight Outage and Crime Rate Analysis with Zach Seeskin

This episode features a discussion with statistics PhD student Zach Seeskin about a project he was involved in as part of the Eric and Wendy Schmidt Data Science for Social Good Summer Fellowship.  Th...

18 Jul 201433min

[MINI] Experimental Design

[MINI] Experimental Design

This episode loosely explores the topic of Experimental Design including hypothesis testing, the importance of statistical tests, and an everyday and business example.

11 Jul 201415min

The Right (big data) Tool for the Job with Jay Shankar

The Right (big data) Tool for the Job with Jay Shankar

In this week's episode, we discuss applied solutions to big data problem with big data engineer Jay Shankar.  The episode explores approaches and design philosophy to solving real world big data busin...

7 Jul 201449min

[MINI] Bayesian Updating

[MINI] Bayesian Updating

In this minisode, we discuss Bayesian Updating - the process by which one can calculate the most likely hypothesis might be true given one's older / prior belief and all new evidence.

27 Jun 201411min

Personalized Medicine with Niki Athanasiadou

Personalized Medicine with Niki Athanasiadou

In the second full length episode of the podcast, we discuss the current state of personalized medicine and the advancements in genetics that have made it possible.

20 Jun 201457min

[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 h...

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 t...

6 Jun 20141h 16min

[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).

30 Mai 201411min

Populært innen Vitenskap

fastlegen
tingenes-tilstand
jss
forskningno
rss-zahid-ali-hjelper-deg
rekommandert
rss-paradigmepodden
sinnsyn
liberal-halvtime
vett-og-vitenskap-med-gaute-einevoll
rss-overskuddsliv
kvinnehelsepodden
nordnorsk-historie
tidlose-historier
villmarksliv
grunnstoffene
rss-inn-til-kjernen-med-sunniva-rose
nevropodden
noen-har-snakket-sammen
fjellsportpodden