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How do you calculate standard deviation without a normal distribution?
Wiki User
∙ 12y ago
You calculate standard deviation the same way as always. You find the mean, and then you sum the squares of the deviations of the samples from the means, divide by N-1, and then take the square root. This has nothing to do with whether you have a normal distribution or not. This is how you calculate sample standard deviation, where the mean is determined along with the standard deviation, and the N-1 factor represents the loss of a degree of freedom in doing so. If you knew the mean a priori, you could calculate standard deviation of the sample, and only use N, instead of N-1.
Wiki User
∙ 12y ago
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When computing Standard deviation should you eliminate the extreme values?
Generally not without further reason. Extreme values are often called outliers. Eliminating unusually high values will lower the standard deviation. You may want to calculate standard deviations with and without the extreme values to identify their impact on calculations. See related link for additional discussion.
What is 2 Standard Deviations above an average of .1407?
The answer depends on the value of the standard deviation. Without that information, the question cannot be answered.
What is meant by dispersion without deviation?
when a ray of light enters two specifically arranged prisms and disperese i.e. splits into characteristic colours without suffering any deviation inside the prisms(the magnitude of deviation for both the prisms is same and in opposite direction, so net deviation is zero); its called dispersion without deviation...
Is it possible for the standard deviation to be less than the sample mean?
Absolutely. In fact I would commonly expect it to be. If, for example, the sample mean for the length of a bolt was 5.5 cm, you would certainly hope the standard deviation was a lot less than 5.5 cm. or it would imply bolts with a negative length (not quite sure how you'd do that without breaching some alternate dimension - no pun intended.)
How can you use statistical measures to compare populations?
There are different methods for comparing the mean, variance or standard error, distribution or other characteristics of populations. Without more specific information it is not possible to answer the question.
What is the middle 95 percent of students who drink five beers with a standard deviation of 01 and a mean of 07?
Not possible to tell you without knowing how many students' there are, and what distribution you wish to use (i.e normal distribution, t-distribution etc...)
When computing Standard deviation should you eliminate the extreme values?
Generally not without further reason. Extreme values are often called outliers. Eliminating unusually high values will lower the standard deviation. You may want to calculate standard deviations with and without the extreme values to identify their impact on calculations. See related link for additional discussion.
What is the stardard deviation for a mean of 4.33?
Without more information, it isn't possible to determine the standard deviation from the mean alone.
Without calculating the standard deviation why does the set 4 4 20 20 have a standard deviation of 8?
The mean is 12 and each observation is 8 units away from 12.
What does relative standard deviation of 0.003 mean?
The relative standard deviation is the absolute value of the ration of the sample mean to the sample standard deviation. This value appears to be quite small; however, without comparative data it is difficult to know what to make of it. In some contexts it might even be considered large.
What is 2 Standard Deviations above an average of .1407?
The answer depends on the value of the standard deviation. Without that information, the question cannot be answered.
What does 2 mean when the means 0?
It is not possible to answer without any information on the spread (range, inter-quartile range, mean absolute deviation, standard deviation or variance).
What role does the Central Limit Theorem play in evaluation of the confidence level or hypothesis testing?
Without getting into the mathematical details, the Central Limit Theorem states that if you take a lot of samples from a certain probability distribution, the distribution of their sum (and therefore their mean) will be approximately normal, even if the original distribution was not normal. Furthermore, it gives you the standard deviation of the mean distribution: it's σn1/2. When testing a statistical hypothesis or calculating a confidence interval, we generally take the mean of a certain number of samples from a population, and assume that this mean is a value from a normal distribution. The Central Limit Theorem tells us that this assumption is approximately correct, for large samples, and tells us the standard deviation to use.
What does the higher standard deviation data set explain?
A higher standard deviation means that the data are fluctuating more widely with respect to the mean. It could mean there are some bad samples, or it could simply mean that the data are not as tightly bound to the mean as anticipated. An unexpected standard deviation should be evaluated, using more robust analyses techniques, so as to differentiate between the various explanations. This is an expected part of error analysis, without which an analysis is incomplete.
What is meant by dispersion without deviation?
when a ray of light enters two specifically arranged prisms and disperese i.e. splits into characteristic colours without suffering any deviation inside the prisms(the magnitude of deviation for both the prisms is same and in opposite direction, so net deviation is zero); its called dispersion without deviation...
What are the applications of dispersion without deviation?
no
What does straightforward mean?
Direct, without deviation.
