School of Biology, University of St Andrews, St Andrews KY16 9TH, UK
Biol Lett. 2017 Jan;13(1). doi: 10.1098/rsbl.2016.0756.
Although circular data are common in biological studies, the analysis of such data is often more rudimentary than it need be. One of the most common hypotheses tested is whether the data suggest that samples are clustered around a certain specified direction, rather than being uniformly spread across all possible directions. Here, I use data from a recent publication on the compass directions of epiphytes and mistletoes on tree trunks. This is used to demonstrate how with relatively little extra work researchers can improve the rigour of testing such hypotheses, and this improved rigour can lead to biological insights missed by simpler analyses. Specifically, I highlight that a much broader range of null hypotheses can be tested than current practice, and that a range of methods are available for estimating a confidence interval for mean direction. I offer advice on appropriate selection for both tests and parameter estimation methods, and highlight the need to correct for the fact that sample estimates are biased estimates of population parameters for circular data.
尽管圆形数据在生物研究中很常见，但对这些数据的分析往往比实际需要的更为基础。其中最常见的假设检验之一是，数据是否表明样本集中在某个特定的方向，而不是均匀分布在所有可能的方向上。在这里，我使用了最近一篇关于树干上附生植物和槲寄生的罗盘方向的出版物中的数据。这用于演示研究人员只需稍加努力，就可以提高测试此类假设的严谨性，而这种改进的严谨性可以带来简单分析错过的生物学见解。具体来说，我强调可以测试比当前实践更广泛的零假设范围，并且有多种方法可用于估计平均方向的置信区间。我就两种检验和参数估计方法的适当选择提供了建议，并强调需要纠正样本估计是对圆形数据的总体参数的有偏估计这一事实。
