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Any deviation would usually be indicative of either faulty equipment or technician error, although there are some conditions that present with high MCV without megaloblastic cells. For further specification, it can be used to calculate red blood cell distribution width (RDW). The RDW is a statistical calculation made by automated analyzers that ...
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] Since RDW-CV is mathematically derived from MCV, it is therefore affected by the average RBC size (MCV). [7]
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 complete blood count (CBC), also known as a full blood count (FBC), is a set of medical laboratory tests that provide information about the cells in a person's blood.The CBC indicates the counts of white blood cells, red blood cells and platelets, the concentration of hemoglobin, and the hematocrit (the volume percentage of red blood cells).
Its standard deviation is 32.9 and its average is 27.9, giving a coefficient of variation of 32.9 / 27.9 = 1.18; In these examples, we will take the values given as the entire population of values. The data set [100, 100, 100] has a population standard deviation of 0 and a coefficient of variation of 0 / 100 = 0
The mean and the standard deviation of a set of data are descriptive statistics usually reported together. In a certain sense, the standard deviation is a "natural" measure of statistical dispersion if the center of the data is measured about the mean. This is because the standard deviation from the mean is smaller than from any other point.
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The "68–95–99.7 rule" is often used to quickly get a rough probability estimate of something, given its standard deviation, if the population is assumed to be normal. It is also used as a simple test for outliers if the population is assumed normal, and as a normality test if the population is potentially not normal.