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    Hoping this is the correct thread.

    Basically, I am trying to work out the standard deviation of rain fall across 12 months (for about 6 decades).

    For example, for the year 1945 I have this (in mm):



    So I thought the standard deviation is just how much the rainfall deviates from the mean value, or from half of the max value. So here, for example, max. rainfall occurs in June at 94.4mm, and the minimum rainfall in another month is 0mm. So isn't the standard deviation just (94.4/2) = + or - 47.2mm a month? Actually that doesn't make sense...you can't get negative rainfall o.o

    But could someone explain the purpose of and calculations for standard deviation please?

    Thank you, much appreciated
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    (Original post by PhysicsGal)
    Hoping this is the correct thread.

    Basically, I am trying to work out the standard deviation of rain fall across 12 months (for about 6 decades).

    But could someone explain the purpose of and calculations for standard deviation please?

    Thank you, much appreciated
    Standard deviation is slightly more complicated than what you've tried.

    Basically, it tries to work out an average spread for the data away from the mean.

    The way the calculation works is as follows:
    first work out the mean
    next work out the difference between each observation and the mean (this can be +ve or -ve)
    square each number from the previous step to ensure you get a positive number
    add up all these squared numbers and divide by the number of observations
    take the square root to get the standard deviation

    The good news is that Excel has functions to calculate this automatically for you (although it is worth doing the calculation for a small dataset so you get used to what's happening).

    Check out the STDEVP (or STDEV.P in Excel 2010) functions.

    Post back if this doesn't make sense
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    It's a measure of the spread of the data and how far some figures are from the mean.
    You might not do this but you can use it to work out which figures are outliers


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