武老师前天提到Mark Buchanan的文章 Enter the matrix: the deep law that shapes our reality，找来浏览了一遍——关于随机矩阵方法，需要另外补课——这会儿是看到有段话很有意思：

While random matrix theory suggests that this is a promising approach, it also points to hidden dangers. As more and more complex data is collected, the number of variables being studied grows, and the number of apparent correlations between them grows even faster. With enough variables to test, it becomes almost certain that you will detect correlations that look significant, even if they aren't.

从随机矩阵发现的关系，不一定都是动力学意义的因果关系，而没有因果的关系——纯粹数据之间的关系——几乎是没有意义的，它可能成为懒人的投机方法，更可恨的是它会遮蔽真实的关系。这种例子很多，多得来我一个都想不起了。