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RDW-SD is calculated as the width (in fL) of the RBC size distribution histogram at the 20% height level. This parameter is, therefore, not influenced by the average RBC size (mean corpuscular volume, MCV). [7] RDW-CV (expressed in %) is calculated with the following formula: RDW-CV = (1 standard deviation of RBC volume ÷ MCV) × 100%. [8]
When the score distribution is approximately normally distributed, sten scores can be calculated by a linear transformation: (1) the scores are first standardized; (2) then multiplied by the desired standard deviation of 2; and finally, (3) the desired mean of 5.5 is added. The resulting decimal value may be used as-is or rounded to an integer.
Mean corpuscular volume (MCV) is the average volume of a red blood cell and is calculated by dividing the hematocrit (Hct) by the concentration of red blood cell count. [citation needed] = [] Normal range: 80–100 fL (femtoliter)
A low standard deviation indicates that the values tend to be close to the mean (also called the expected value) of the set, while a high standard deviation indicates that the values are spread out over a wider range. The standard deviation is commonly used in the determination of what constitutes an outlier and what does not.
This may also be called standard range. In contrast, optimal (health) range or therapeutic target is a reference range or limit that is based on concentrations or levels that are associated with optimal health or minimal risk of related complications and diseases. For most substances presented, the optimal levels are the ones normally found in ...
The standard definition of a reference range for a particular measurement is defined as the interval between which 95% of values of a reference population fall into, in such a way that 2.5% of the time a value will be less than the lower limit of this interval, and 2.5% of the time it will be larger than the upper limit of this interval, whatever the distribution of these values.
It is the mean divided by the standard deviation of a difference between two random values each from one of two groups. It was initially proposed for quality control [1] and hit selection [2] in high-throughput screening (HTS) and has become a statistical parameter measuring effect sizes for the comparison of any two groups with random values. [3]
The data set [90, 100, 110] has more variability. Its standard deviation is 10 and its average is 100, giving the coefficient of variation as 10 / 100 = 0.1; The data set [1, 5, 6, 8, 10, 40, 65, 88] has still more variability. Its standard deviation is 32.9 and its average is 27.9, giving a coefficient of variation of 32.9 / 27.9 = 1.18