Statistics Quiz#1

[Richard Wallace]

Originally Posted by Tristan Lall

I have a feeling there's a story behind this. Anything you can share?

(I'd say statistics are extremely useful in quality management for high-volume production, in processes that have already been well-characterized and refined. But that's probably not the scenario being criticized.)

You're right, Tristan -- there are many engineering situations that call for statistical inference; e.g.,

-- quantum models for very small scale material properties - as Michael Hill pointed out above, this is a special case for which statistics is an indispensible part of physics,

-- developing strategies for playing games of chance,

-- detection and ranging methods to extract useful signals in the presence of background noise, and

-- optimizing large scale serial manufacturing processes by isolating defect causes that arise due to variation of many potentially interacting factors.

In each of these situations, the challenging aspect is random variation in the observed data.

However, there are many more engineering situations in which statistical inference is not the best tool. The scenario I was criticizing above arises when an engineer tries to use statistical inference to understand patterns in observed data that are not random at all, but instead are based on physical principles the the engineer has failed to recognize -- in such situations the challenge is not random variation, it is ignorance.

Ignorance cannot be overcome by statistical inference.