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How many standard deviations is 16.50 from the mean?

How many standard deviations is 16.50 from the mean?


This tells how many standard deviations a measurement is away from the mean?

Z-Score tells how many standard deviations a measurement is away from the mean.


How many pages does Perfectly Reasonable Deviations from the Beaten Track have?

Perfectly Reasonable Deviations from the Beaten Track has 486 pages.


How would you identify and report deviations and what is the significance of deviations?

identify and report deviations


What is the sum of the deviations from the mean?

The sum of standard deviations from the mean is the error.


How many standard deviations is 19 from the mean?

That depends on what the standard deviation is.


How many standard deviations above the mean is the 90th percentile?

It is 1.28


What is the z-score of a value that is 2.08 standard deviations greater than the mean?

The z-score of a value indicates how many standard deviations it is from the mean. If a value is 2.08 standard deviations greater than the mean, its z-score is simply 2.08. This means the value lies 2.08 standard deviations above the average of the dataset.


Tells how many standard deviations a measurement is away from the mean?

z score


How many standard deviations is 99?

You cannot have a standard deviation for 1 number.


How many standard deviations are 95 percent of measurements away from the mean?

95 percent of measurements are less than 2 standard deviations away from the mean, assuming a normal distribution.


Why use the squarred version of the sum of deviations from the mean?

You cannot use deviations from the mean because (by definition) their sum is zero. Absolute deviations are one way of getting around that problem and they are used. Their main drawback is that they treat deviations linearly. That is to say, one large deviation is only twice as important as two deviations that are half as big. That model may be appropriate in some cases. But in many cases, big deviations are much more serious than that a squared (not squarred) version is more appropriate. Conveniently the squared version is also a feature of many parametric statistical distributions and so the distribution of the "sum of squares" is well studied and understood.