I read the Wheeler's Workshop column in your magazine each month, with keen interest. However, in the May 2001 issue (p. 26), I found a comment in the "April Brain Teaser" section that is disconcerting. The comment was in regard to rounding of data values, and how excessive data rounding can lead to an incorrect standard deviation. I have found that frequently the data presented in the questions in this section will contain a certain number of significant figures--usually reflecting some measurement process or another, whether it is length, area, weight or whatever. But, when the average of the data is computed, and following this, the standard deviation, the answer is presented with quite a few more significant figures than any of the individual data points. This is incorrect, as it implies a level of knowledge that you don't have. By this, I mean that if you were to measure 100,000 items for length to the nearest 0.1-inch, not to 5 decimals or more to the right. This stands to reason, because all of the individual measurements are to the nearest 0.1-inch. Any smaller units, such as 0.001-inch or 0.01-inch are not gathered at all. If you were to measure a population of 10,000,000 of these items, you would expect that the most frequent value of length would be the average. You would further expect that if the population is normally distributed, such as gaussian distribution, that about 99.97 percent of all measurements would be within plus or minus 3 standard deviations of the average value. Again, you can see that the standard deviation really cannot be expressed with more decimals to the right than the smallest unit measured, in this case, 0.1-inch, because there is no knowledge of any significant figure more than 1 to the right. In this fashion, the length could be confidently stated to be xx.yI0.z inches, where z is 3 standard deviations to the nearest 0.1-inch. Again, reflecting measurement limitations, with 99.97 percent certainty. My degree is a Bachelor of Science in Chemistry, and as part of data handling, we were taught how to treat significant figures before further processing, and how to present averages and standard deviations, as well as how to correctly calculate these items.