Journal
ECOSPHERE
Volume 4, Issue 9, Pages -Publisher
WILEY
DOI: 10.1890/ES13-00160.1
Keywords
confidence intervals; errors; experimental design; graphing; mistakes; p values; statistics education
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The most common statistical pitfalls in ecological research are those associated with data exploration, the logic of sampling and design, and the interpretation of statistical results. Although one can find published errors in calculations, the majority of statistical pitfalls result from incorrect logic or interpretation despite correct numerical calculations. There are often simple solutions to avoiding these problems that require only patience, clarity of thinking, probabilistic insight, and a reduced reliance on out-of- the-box approaches. Some of these trouble spots are inherent to all statistical analyses and others are particularly insidious in ecology where true controls or replication are challenging, small sample sizes are common, and correctly linking mathematical constructs and ecological ideas is essential. Here we summarize the most common statistical pitfalls observed over nearly a century of combined consulting and research experience in ecological statistics. We provide short, simple solutions.
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