Vieland Veronica J
The Research Institute at Nationwide Children's Hospital and The Ohio State University, Columbus, Ohio, USA.
Hum Hered. 2014;78(3-4):153-63. doi: 10.1159/000367599. Epub 2014 Oct 30.
A primary purpose of statistical analysis in genetics is the measurement of the strength of evidence for or against hypotheses. As with any type of measurement, a properly calibrated measurement scale is necessary if we want to be able to meaningfully compare degrees of evidence across genetic data sets, across different types of genetic studies and/or across distinct experimental modalities. In previous papers in this journal and elsewhere, my colleagues and I have argued that geneticists ought to care about the scale on which statistical evidence is measured, and we have proposed the Kelvin temperature scale as a template for a context-independent measurement scale for statistical evidence. Moreover, we have claimed that, mathematically speaking, evidence and temperature may be one and the same thing. On first blush, this might seem absurd. Temperature is a property of systems following certain laws of nature (in particular, the 1st and 2nd Law of Thermodynamics) involving very physical quantities (e.g., energy) and processes (e.g., mechanical work). But what do the laws of thermodynamics have to do with statistical systems? Here I address that question.
遗传学中统计分析的一个主要目的是衡量支持或反对假设的证据强度。与任何类型的测量一样，如果我们希望能够有意义地比较不同遗传数据集、不同类型的遗传研究和/或不同实验模式之间的证据程度，就需要一个校准恰当的测量尺度。在本期刊及其他地方之前发表的论文中，我和我的同事们认为，遗传学家应该关注统计证据的测量尺度，并且我们已经提出开尔文温度尺度作为统计证据的与上下文无关的测量尺度的模板。此外，我们声称，从数学角度来讲，证据和温度可能是同一回事。乍一看，这似乎很荒谬。温度是遵循某些自然规律（特别是热力学第一定律和第二定律）的系统的一种属性，涉及非常物理的量（例如能量）和过程（例如机械功）。但是热力学定律与统计系统有什么关系呢？在此我将探讨这个问题。
