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Statistics for Wildlifers: How much and what kind?

Introduction


Most students who choose a major in wildlife biology probably do so because of their interest in nature and the outdoors. Mention a career as a wildlife biologist and many folks immediately envision a person who works outdoors observing wildlife and taking notes, not interpreting a mathematical equation or estimating the probability of some event. The notion that coursework in mathematics and statistics is recommended, and in most cases even required, for a degree in wildlife biology may seem absurd to a prospective student. Indeed, students even may be drawn to the wildlife field because, in addition to enjoying the subject, they perceive it as being insulated from mathematics, perhaps their least favorite subject in high school. As is often the case, however, reality does not match perception.

Our article is intended primarily for college students who aspire to become wildlife biologists, especially those interested in a research career and secondarily for the professors who advise, train, and mentor those students. We offer it from our perspective as statisticians who work for a federal wildlife research center. Each of us was recruited by the Northern Prairie Wildlife Research Center to provide statistical support for its research program. Together, we have 60 years of experience at the Center. Each of us has consulted with dozens of research and management biologists from federal, state, university, and private institutions, and supervised other statisticians who consulted with biologists. We currently supervise wildlife researchers, and provide statistical advice. We have worked with biologists of widely diverse quantitative backgrounds, from individuals with little or no statistical background to those with graduate degrees in statistics. The ideas we present here are derived from these experiences. By sharing them we hope to provide insight into the ways wildlife biologists use statistics in their work and the sort of statistical education we believe is appropriate and most beneficial.


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