In lieu of an abstract, here is a brief excerpt of the content:

  • Critical Notice1
  • Ingo Brigandt (bio)
Elliott Sober , Evidence and Evolution: The Logic Behind the Science. Cambridge: Cambridge University Press 2008. Pp. xx + 392.

As Elliott Sober acknowledges in the preface, the title of his latest book, Evidence and Evolution, is potentially confusing, for his discussion does not present various known empirical facts that support the theory of common ancestry, such as fossil data and genetic and anatomical features of extant species. Rather, it is an epistemological study of scientific inference and the confirmation of hypotheses in the context of evolutionary biology. Sober targets a dual audience. Philosophers will obtain from his detailed and convincing account general lessons on the nature of confirmation and an introduction to or overview of basic models in evolutionary theory. Biologists will benefit as well, since Sober steps back from the variety of existing quantitative models and identifies common strands in hypothesis testing and addresses how to justify certain fundamental assumptions that biologists often take for granted. Below I will highlight two philosophical themes that run through Sober's discussion. Sober has made these point more than once in previous work (Sober 1988, 1999, 2007), but they are of central importance and cannot be repeated often enough. These are the facts that (1) confirmation in science is contrastive, where a theory can be [End Page 159] meaningfully tested only against one or more rival hypotheses, and (2) scientific inference methods are not a priori and valid for every case, but presuppose specific empirical assumptions and thus are legitimate only in a certain range of empirical cases.

Apart from a conclusion, the book is divided into four long chapters (each of which is organized into several sections). Chapter 1 discusses different schools of hypothesis testing, including Bayesianism, likelihoodism, and frequentism. Chapter 2 addresses how the intelligent design hypothesis fares against evolutionary theory. Biologists especially may wonder what the point is of discussing a hypothesis without scientific merit. Yet Sober's account has implications for the confirmation of evolutionary theory and the testing of scientific theories in general, so that some of his major philosophical moves are made in this context. The subsequent chapter discusses how the tenet that a biological character is the result of natural selection can be tested against alternatives, such as being the outcome of random drift. Chapter 4 concerns common ancestry. While most biological accounts test different phylogenetic trees against each other, Sober focuses on how the very hypothesis that extant species have a common ancestry rather than independent origins can be confirmed.

To understand Sober's main thesis, let us take a look at Chapter 1, which offers a general discussion of the impact of evidence by comparing Bayesianism, likelihoodism, and frequentism. These approaches are not to be understood as different semantic or metaphysical interpretations of probabilities, but as different epistemological methods of scientific inference. Bayesianism offers an account of to what degree a hypothesis H should be believed, and how to change this degree of belief in light of new observational evidence O in accordance with Bayes's theorem: P(HO) = P(OH)/P(O).P(H). One problem with Bayesianism is that in many concrete cases it is impossible to assign a non-arbitrary prior probability / degree of belief P(H) (from which to objectively update the degree of belief based on further evidence). Likelihoodism has the advantage that it can do without subjective priors, as it focuses on the likelihood P(O.H), i.e., how probable a certain observation O is according to hypothesis H. Likelihoodism gets traction by comparing the likelihoods of two or more hypotheses. If P(O.H1) > P(O.H2), then observation O favours H1 over H2; and among a set of rival hypotheses, there may be one that is favoured over all others. However, while Bayesianism — if it is applicable — offers an answer to the question of which hypothesis to believe (at least to which degree), likelihoodism as such does not tell us what we should believe, it rather tells us what the evidence says (vis-à-vis one or several hypotheses, 32). [End Page 160]

Frequentism is not one inference method, but encompasses several different methods. One well...

pdf

Additional Information

ISSN
1911-0820
Print ISSN
0045-5091
Pages
pp. 159-186
Launched on MUSE
2011-05-25
Open Access
No
Archive Status
Archived
Back To Top

This website uses cookies to ensure you get the best experience on our website. Without cookies your experience may not be seamless.