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*To*: "'IP List'" <email @ redacted>*Subject*: RE: [IP] Dropping*From*: "Handsfield, James H." <email @ redacted>*Date*: Fri, 7 Apr 2000 08:11:01 -0400*Reply-To*: email @ redacted

Pixie <email @ redacted> wrote: > Normal is individual, there's no standard "how much of a drop > is normal in what period of time" hence, there is technically > no safety amount, it varies from person to person. < Professional Mode = ON > Actually, normal is *not* individual. Normal is usually a synonym for the mean -- the central tendency of a group of measurements, in this case rate of reduction in blood glucose per unit of H. The whole concept of YMMV depends on the measurements of "normal" (and there are several ways that can be measured) along with the variability of those measurements. Technically, a normal distribution is one in which we see a classic "bell curve" of responses which can be transformed to the "standard normal" with a mean of zero and a standard deviation of one. We also deal with confidence intervals, most commonly a 95% confidence interval. That means that in a normal (also called Gaussian) distribution, any point that falls within ninety-five percent of the *area* of the curve is confidently deemed to have the same value as the mean. In a true normal distribution, this 95% confidence level is equivalent to two standard deviations on either side of the mean. That's why we are often given a *range* of normal values, and told whether our own measurements fall within that range. When we calculate "normal" values, we make an inherent assumption -- that the numbers we see are representative of *everyone* in the class we are measuring. That may be all people, or people with diabetes, or people with type 1, or people with type 2, etc., etc. IOW, we have to define the basis for our statement of normalcy. Normal for a type 1 may not be the same as normal for type 2, etc. But (and it's a big but, and very important): these are not statements of judgment of value -- only statements of the way things are. Normal does not mean good or bad. Normal is morally, medically, ethically, etc. NEUTRAL. With some statistical procedures, we are able, by making a couple of assumptions, to *infer* what might happen at some future time based on the data we see now. This is usually expressed as a likelihood, probability, or, most commonly, a RISK. For example, there is a statistical association between having diabetes and heart disease. So we say that diabetics have five times the risk of non-diabetics with no history of heart disease of having a heart attack (myocardial infarction). That does NOT mean that all diabetics are going to have a heart attack (there are ways to reduce the risk!). What it DOES say is that in the past, diabetics have had heart attacks at five times the rate of non-diabetics who have no other indications of heart disease, and, because we can make some assumptions about the distributions, that the rate we have seen in the past will continue *IF NO OTHER FACTORS CHANGE*. To sum up, this is the basic concept behind YMMV. Not one of us is normal. We may have measurements that are normal, that is close to the mean (or other central measure) of the population, but that is just one measurement out of many that make up normal. Because that determination is made with the confidence interval in mind, most often we are given a *range* of normal and told whether our measurements fall within that range. If you're still here, thank you. I hope this is helpful to you. < Professional Mode = OFF > Jim Handsfield Statistician Centers for Disease Control and Prevention mailto:email @ redacted OR mailto:email @ redacted The opinions expressed are my own and do not necessarily represent those of the Centers for Disease Control and Prevention, the United States Public Health Service or any other agency of the United States government. ---------------------------------------------------------- for HELP or to subscribe/unsubscribe, contact: HELP@insulin-pumpers.org send a DONATION http://www.Insulin-Pumpers.org/donate.shtml

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