4 ms·

Why doesn't randomization defeat dimensionality?

• lmkg 12y ago
  Randomization lets you ignore dimensions that you're not interested in. It doesn't do much in the way of letting you attribute an effect to one or more dimensions from a large set of them. There's a fundamental lower bound to the number of data-points you need to make in order to achieve statistical significance. This lower bound grows exponentially in the number of dimensions, particularly if you cannot make the simplifying assumption that the dimensions are statistically independent (and biological systems are often coupled in strange ways). Randomization is a good way of achieving that lower bound, but it cannot defeat it.