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The first thing you do, in any stats analysis, is calculate the mean, call it M.
Then to find the standard deviation, you want to find something called "Variance."
That is a measure of how spread the data points are from the Mean.
You calculate that by first calculating how far each of the data points are from M. Then you square each of those quantities. Then you sum it all up to the the total Variance.
So here, you'd want to add up (100 - M)^2 + (95 - M)^2 + ... + (3 - M)^2 + (4 - M)^2.
The Standard Deviation is just the square of the Variance.
So then you take the square root of that sum you calculated.
it is population standard deviation
and can you take a look at my other 2 problems please
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Your population standard deviation is the standard deviation when you use all the numbers.
A sample standard deviation is the standard deviation when you only look at a portion of the population, take the mean of that portion, and find the variance for that portion of the population.
So the population standard deviation is what I wrote above.