The term "ANOVA" is am acronym for the "analysis of variance", a powerful statistical technique.

I'll illustrate by a very significant case, which has received little attention. It sppears in Quality Control and Industrial Statistics, by Acheson J. Duncan, 1955.

It deals with a article by Grant Wernimont, "Quality Control in the Chemical Industry", in Industrial Quality Control, May, 1947. The data concerns the melting point of hydroquinone (a chemical used in developing photographs). Naturally, different measurements may differ, so an arithmetic mean value is calculated, also the variance about the mean. (If the variance is small, then the mean value is considered to be "fairly precise".) The problem considered is how to explain some of this variance due to known varying factors in the experimental situation, allowing reduction of the variance.

After reviewing the data, some experimental differences are noticed:

Three different thermometers were used. It's found that some difference can be explained by difference in thermometer, so the variance value is reduced.

Then it was noted that three different observers were involved. It's found that some diffference can be explained by difference in observer, so the variance value is further reduced, making the mean value seem more precise.

Finally, it was noted that observations took place at decidedly different periods of the day. But this could not explain the variation, so the report was fixed. This case did not result in total explanation of the variance, but did result in partial explanation, which was an accomplishment.

That's all I'm trying to do in this presentation. To explain part of the "strangeness" of quantics. Feynman once said that no one could understant quantics. But I've shown that several "clues" have been overlooked. (Perhaps others may extend this explication.)