Suppose the random variable W represents the weight, and assume that W is Normally distributed with the given mean and standard deviation.
Then Prob(140 < W < 220) = Prob[(140 - 145)/31 < Z < (220 - 145)/31]
where Z has a standard Normal distribution.
that is, Prob(-0.1613 < Z < 2.4194) = 1 - [Prob(-0.1613 < Z) + Prob(Z < 2.4194)
= 1 - (0.4359 + 0.0078) = 0.5563
So percentage of women = 100*0.5563 = 56% approx.
34.1% with the normal distribution.
Standard deviation is the variance from the mean of the data.
The mean is the average value and the standard deviation is the variation from the mean value.
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The mean deviation for any distribution is always 0 and so conveys no information whatsoever. The standard deviation is the square root of the variance. The variance of a set of values is the sum of the probability of each value multiplied by the square of its difference from the mean for the set. A simpler way to calculate the variance is Expected value of squares - Square of Expected value.
Standard deviation doesn't have to be between 0 and 1.
Standard deviation is the square root of the variance.
34.1% with the normal distribution.
Standard deviation is the variance from the mean of the data.
You can calculate standard deviation by addin the numbers of data that are together and dividing that number by the amount pieces of data.THAT IS TOTALLY INCORRECT.What was answered above was the calculation for getting an (mean) average.If you take five numbers for example 1, 2, 3, 4, 5 then the (mean) average is 3.But the standard deviation between them is 1.58814 and the variance is 2.5Also the population std. deviation will be 1.41421 and the population variance will be 2.see standard-deviation.appspot.com/
Standard error of the mean (SEM) and standard deviation of the mean is the same thing. However, standard deviation is not the same as the SEM. To obtain SEM from the standard deviation, divide the standard deviation by the square root of the sample size.
The distance between the middle and the inflection point is the standard deviation.
The standard deviation is the square root of the variance.
The mean is the average value and the standard deviation is the variation from the mean value.
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The area between the mean and 1 standard deviation above or below the mean is about 0.3413 or 34.13%
The more precise a result, the smaller will be the standard deviation of the data the result is based upon.