Northern Prairie Wildlife Research Center
An appreciation of statistical issues is valuable when reviewing the literature on the topic one intends to address in a new study. Which of the extant studies are solid and provide a useful basis for further work? Which are based on weak data, inappropriate analyses, or unsubstantiated interpretations, and therefore should be given little credence? These considerations are equally important to a wildlife manager who is reviewing research findings and judging their relevance to particular management situations.
Statistical thinking is also important during the data collection phase of a research or management study. A statistically minded biologist will be better able to detect unanticipated problems with the study design than will a biologist who is statistically unaware. This can be as simple as recognizing an important but unaccounted-for source of variation and deciding to record an additional variable that can be used as a covariate during data analysis. Or, the biologist may realize early on that 2 or more experimental units are not responding independently of one another and take necessary steps either to replace one of the units or at least to account for the lack of independence during data analysis. An appreciation of statistics will help the investigator recognize when sample sizes are insufficient to achieve objectives. In the most extreme situation, this can lead to the early termination of a study that is destined to fail and a savings of resources that would otherwise have been wasted.
Knowledge of statistics is obviously helpful during the data analysis and manuscript preparation stages. Knowing which analyses to perform, and why, along with understanding and assessing the assumptions underlying those analyses and being able to interpret the results are of critical importance. In addition to accurately describing the statistical methods in the manuscript, biologists need to know such things as if a P-value is appropriate or not and when to report a standard deviation as opposed to a standard error. Managers will call upon their statistical understanding to help them interpret results of research studies or management evaluations and to determine how much confidence they should place in those results.
The final juncture at which statistical knowledge can be useful is when considering comments from reviewers, whether they be referees of manuscripts or teams reviewing management strategies. Some comments by reviewers, including those that pertain to statistical analyses, are of enormous value; others may have little or no utility. No one knows the data better than the person who collected, analyzed, and interpreted them. Being able to judge the appropriateness of reviewer comments and recommendations is essential for choosing an appropriate analysis and developing a high-quality manuscript or resource management plan.