An interview with ICES guest instructor Ray Hilborn
All about Bayesian inference in fisheries science
ICES Training Programme recently offered Introduction to Bayesian Inference in Fisheries Science, conducted by Ray Hilborn and Samu Mäntyniemi. It was attended by 26 students from 17 countries.
Ray Hilborn, one of today’s leading experts on fisheries, is a professor in the School of Aquatic and Fishery Sciences, University of Washington, specializing in natural resource management and conservation. He serves as an advisor to several international fisheries commissions and agencies as well as teaching graduate and undergraduate courses in conservation, fishery stock assessment, and risk analysis. He is author of Quantitative Fisheries Stock Assessment, with Carl Walters, and The Ecological Detective: Confronting Models with Data, with Marc Mangel.
What is Bayesian statistics?
Bayesian statistics is one variety of statistics. Depending on how you divide it, you could say there are three primary schools. Beginning statistics courses centre on the concept of the null hypothesis and whether the data support rejection of the null hypothesis; usually, statistics are reported so that the probability of the null hypothesis is false. Then, there is the probability that you can reject the null hypothesis, and that’s often called Frequentive statistics. Finally, there’s another school, the Likelihoodist, that deals primarily with the extent to which the data support competing hypotheses. It’s a more interesting statistic because it realizes that you often have multiple different hypotheses, which is interesting to the extent that the data support the different hypotheses.
Bayesian statistics is, in a sense, much like the Likelihoodist, but it goes the additional step of actually assigning probabilities to competing hypotheses. The reason that’s so important is that, when you are giving advice to decision-makers, they want to know what’s the chance that something will happen. It turns out that Bayesian statistics is the only form of statistics that philosophically claims that they are probabilities. Going back – I guess I first ran into Bayesian statistics about 35 years ago – you find that Bayesian statistics really dominated business schools because they were built around decision-making.
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