The standard deviation of the population. the standard deviation of the population.
The standard deviation is a number that tells you how scattered the data are centered about the arithmetic mean. The mean tells you nothing about the consistency of the data. The lower standard deviation dataset is less scattered and can be regarded as more consistent.
The standard deviation is 0.
The standard deviation in a standard normal distribution is 1.
You need more than one number to calculate a standard deviation, so 9 does not have a standard deviation.
Square the standard deviation to obtain the variance. The variance is 62 or 36.
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The standard deviation is the standard deviation! Its calculation requires no assumption.
The range is 9 and 3.01 is the standard deviation.
The standard deviation of the population. the standard deviation of the population.
The standard deviation is a number that tells you how scattered the data are centered about the arithmetic mean. The mean tells you nothing about the consistency of the data. The lower standard deviation dataset is less scattered and can be regarded as more consistent.
Strictly speaking, none. A quartile deviation is a quick and easy method to get a measure of the spread which takes account of only some of the data. The standard deviation is a detailed measure which uses all the data. Also, because the standard deviation uses all the observations it can be unduly influenced by any outliers in the data. On the other hand, because the quartile deviation ignores the smallest 25% and the largest 25% of of the observations, there are no outliers.
The standard deviation is 0.
Information is not sufficient to find mean deviation and standard deviation.
Standard deviation is the square root of the variance.
The standard deviation in a standard normal distribution is 1.
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.