Bayes in biological anthropology.

Lyle W Konigsberg, Susan R. Frankenberg

Research output: Contribution to journalReview article

Abstract

In this article, we both contend and illustrate that biological anthropologists, particularly in the Americas, often think like Bayesians but act like frequentists when it comes to analyzing a wide variety of data. In other words, while our research goals and perspectives are rooted in probabilistic thinking and rest on prior knowledge, we often proceed to use statistical hypothesis tests and confidence interval methods unrelated (or tenuously related) to the research questions of interest. We advocate for applying Bayesian analyses to a number of different bioanthropological questions, especially since many of the programming and computational challenges to doing so have been overcome in the past two decades. To facilitate such applications, this article explains Bayesian principles and concepts, and provides concrete examples of Bayesian computer simulations and statistics that address questions relevant to biological anthropology, focusing particularly on bioarchaeology and forensic anthropology. It also simultaneously reviews the use of Bayesian methods and inference within the discipline to date. This article is intended to act as primer to Bayesian methods and inference in biological anthropology, explaining the relationships of various methods to likelihoods or probabilities and to classical statistical models. Our contention is not that traditional frequentist statistics should be rejected outright, but that there are many situations where biological anthropology is better served by taking a Bayesian approach. To this end it is hoped that the examples provided in this article will assist researchers in choosing from among the broad array of statistical methods currently available.

Original languageEnglish (US)
Pages (from-to)153-184
Number of pages32
JournalAmerican journal of physical anthropology
Volume152 Suppl 57
StatePublished - Jan 1 2013

Fingerprint

Bayes Theorem
Anthropology
anthropology
Archaeology
statistics
Forensic Anthropology
Statistical Models
statistical method
computer simulation
Research
Computer Simulation
programming
confidence
Research Personnel
Confidence Intervals
knowledge

ASJC Scopus subject areas

  • Anatomy
  • Anthropology

Cite this

Bayes in biological anthropology. / Konigsberg, Lyle W; Frankenberg, Susan R.

In: American journal of physical anthropology, Vol. 152 Suppl 57, 01.01.2013, p. 153-184.

Research output: Contribution to journalReview article

Konigsberg, LW & Frankenberg, SR 2013, 'Bayes in biological anthropology.', American journal of physical anthropology, vol. 152 Suppl 57, pp. 153-184.
Konigsberg, Lyle W ; Frankenberg, Susan R. / Bayes in biological anthropology. In: American journal of physical anthropology. 2013 ; Vol. 152 Suppl 57. pp. 153-184.
@article{ef81209c87374d2c8aa9362677647626,
title = "Bayes in biological anthropology.",
abstract = "In this article, we both contend and illustrate that biological anthropologists, particularly in the Americas, often think like Bayesians but act like frequentists when it comes to analyzing a wide variety of data. In other words, while our research goals and perspectives are rooted in probabilistic thinking and rest on prior knowledge, we often proceed to use statistical hypothesis tests and confidence interval methods unrelated (or tenuously related) to the research questions of interest. We advocate for applying Bayesian analyses to a number of different bioanthropological questions, especially since many of the programming and computational challenges to doing so have been overcome in the past two decades. To facilitate such applications, this article explains Bayesian principles and concepts, and provides concrete examples of Bayesian computer simulations and statistics that address questions relevant to biological anthropology, focusing particularly on bioarchaeology and forensic anthropology. It also simultaneously reviews the use of Bayesian methods and inference within the discipline to date. This article is intended to act as primer to Bayesian methods and inference in biological anthropology, explaining the relationships of various methods to likelihoods or probabilities and to classical statistical models. Our contention is not that traditional frequentist statistics should be rejected outright, but that there are many situations where biological anthropology is better served by taking a Bayesian approach. To this end it is hoped that the examples provided in this article will assist researchers in choosing from among the broad array of statistical methods currently available.",
author = "Konigsberg, {Lyle W} and Frankenberg, {Susan R.}",
year = "2013",
month = "1",
day = "1",
language = "English (US)",
volume = "152 Suppl 57",
pages = "153--184",
journal = "American Journal of Physical Anthropology",
issn = "0002-9483",
publisher = "Wiley-Liss Inc.",

}

TY - JOUR

T1 - Bayes in biological anthropology.

AU - Konigsberg, Lyle W

AU - Frankenberg, Susan R.

PY - 2013/1/1

Y1 - 2013/1/1

N2 - In this article, we both contend and illustrate that biological anthropologists, particularly in the Americas, often think like Bayesians but act like frequentists when it comes to analyzing a wide variety of data. In other words, while our research goals and perspectives are rooted in probabilistic thinking and rest on prior knowledge, we often proceed to use statistical hypothesis tests and confidence interval methods unrelated (or tenuously related) to the research questions of interest. We advocate for applying Bayesian analyses to a number of different bioanthropological questions, especially since many of the programming and computational challenges to doing so have been overcome in the past two decades. To facilitate such applications, this article explains Bayesian principles and concepts, and provides concrete examples of Bayesian computer simulations and statistics that address questions relevant to biological anthropology, focusing particularly on bioarchaeology and forensic anthropology. It also simultaneously reviews the use of Bayesian methods and inference within the discipline to date. This article is intended to act as primer to Bayesian methods and inference in biological anthropology, explaining the relationships of various methods to likelihoods or probabilities and to classical statistical models. Our contention is not that traditional frequentist statistics should be rejected outright, but that there are many situations where biological anthropology is better served by taking a Bayesian approach. To this end it is hoped that the examples provided in this article will assist researchers in choosing from among the broad array of statistical methods currently available.

AB - In this article, we both contend and illustrate that biological anthropologists, particularly in the Americas, often think like Bayesians but act like frequentists when it comes to analyzing a wide variety of data. In other words, while our research goals and perspectives are rooted in probabilistic thinking and rest on prior knowledge, we often proceed to use statistical hypothesis tests and confidence interval methods unrelated (or tenuously related) to the research questions of interest. We advocate for applying Bayesian analyses to a number of different bioanthropological questions, especially since many of the programming and computational challenges to doing so have been overcome in the past two decades. To facilitate such applications, this article explains Bayesian principles and concepts, and provides concrete examples of Bayesian computer simulations and statistics that address questions relevant to biological anthropology, focusing particularly on bioarchaeology and forensic anthropology. It also simultaneously reviews the use of Bayesian methods and inference within the discipline to date. This article is intended to act as primer to Bayesian methods and inference in biological anthropology, explaining the relationships of various methods to likelihoods or probabilities and to classical statistical models. Our contention is not that traditional frequentist statistics should be rejected outright, but that there are many situations where biological anthropology is better served by taking a Bayesian approach. To this end it is hoped that the examples provided in this article will assist researchers in choosing from among the broad array of statistical methods currently available.

UR - http://www.scopus.com/inward/record.url?scp=85027926568&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85027926568&partnerID=8YFLogxK

M3 - Review article

VL - 152 Suppl 57

SP - 153

EP - 184

JO - American Journal of Physical Anthropology

JF - American Journal of Physical Anthropology

SN - 0002-9483

ER -