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680
4%
6/138
925
5%
7/138
950
22%
30/138
975
59%
81/138
997
3%
4/138
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In a normally distributed sample, 95% of the observations are expected to fall within 2 standard deviations of the mean (950 people); however, when asked how many observations are below 2 standard deviations above the mean, 2.5% of the population less than 2 standard deviations (1/2 of the 5% not included in the 2 standard deviation population) would also be included (total of 975 people). The utility of using normal curves in biostatistics is the ability to rely on certain characteristics of the normal distribution (see Rosner, below). Since this sample's standard deviation is 50 mg/dL, the values of 100 and 300 mg/dL are each 2 standard deviations above and below the mean of 200 mg/dL. Rosner defines one property of the normal distribution as such: 68%, 95%, and 99.7% of observations can be expected to fall within 1, 2, and 3 standard deviations respectively of the mean. Illustration A displays a normal statistical distribution. Incorrect answers: Answer 1: 680 people fall within 1 standard deviation of the mean. Answer 2: 925 people does not represent all patients greater than 2 standard deviations above the mean. Answer 3: 950 people fall within 2 standard deviations of the mean Answer 5: 997 people fall within 3 standard deviations of the mean.
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