normal distribution curve


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Fig. 231 Normal distribution curve .

normal distribution curve

or

Gaussian curve

the bell-like shape produced when a ‘normal’ population is sampled for a continuously varying character (e.g. height in humans) and the FREQUENCY DISTRIBUTION plotted on a graph. The curve is theoretically exactly symmetrical, so that the shape on each side of the mean is the mirror image of the other, with an equal area. See Fig. 231 . Thus the MODE, MEDIAN, and ARITHMETIC MEAN are all at the centre of the distribution. The curve shows the frequency of recorded height in a ‘normal’ population of humans.
References in periodicals archive ?
Particularly with higher sigma levels, the analysis needs to move beyond assuming a normal distribution curve. IIoT platforms provide a broad set of analytics.
Figure 4(b) also shows that data are following a normal distribution curve.
Generally the normal distribution curve is forcibly fitted to the data and based on that marks are normalised.
Here the demand is considered as two different cases for the limits of o.67std, 1std, 2std, 3std of the normal distribution curve. In the first case sudden raise of the demand is considered from mean to upper limit and x is calculated in terms of percentage.
Until recently, grade boundaries were set then checked using the normal distribution curve to make sure approximately the same number of candidates were awarded the same grades each year.
This is because the area under the normal distribution curve out to the standard deviation point is 0.341.