What is standard variation and why is it the square root of the variance?
the standard deviation is a special type of mean, it measures the dispersion of items ie. how far numbers are moving away from the mean \[x_{i}-mean\] but since some numbers can deviate negetively the result has to be squared. the average of the squared result is the varience \[\sum(x-mean)^2/n\] the sd is the square root of the varience because those number were initially unsquared we squared them to avoid adding negetives
What would this be in terms of bell curves? Surely you would have to factor in the probability at x along with how far it deviates from x, some thing like \[P(x) (x-m)^2\]
Also, I take it that the SD is the square root of the variance rather than the variance the square of the SD (ie- the Standard deviation is an absolute value also)?
Join our real-time social learning platform and learn together with your friends!