依赖于数据的统计分析,一个“小径分岔花园”的问题解释了为何许多具有统计学意义的比较并不是那么地靠谱。现今,人们越来越多的意识到,一些科技出版物中的所谓“具有统计学意义”的宣称,往往可能是不太靠谱的。研究人员通常对p值数据很有信心,p值(概率)是一种随机变化的观察结果,即对数据集提供的证据与零假设进行比较的一种统计测量方法。按照惯例,p值低于0.05被认为是对零假设的 Depending on the statistical analysis of the data, the question of a “small-scale bifurcated garden” explains why many statistically significant comparisons are not as reliable. Nowadays, people are more and more aware that the so-called “statistically significant” claims in some scientific and technological publications may not always be reliable. Researchers are generally confident in p-value data, a random change in observation that provides a statistical measure of the evidence provided against a dataset against a null hypothesis. By convention, a p-value below 0.05 is assumed to be null hypothesis