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Suppose the probability density function is f(x), defined over a domain D
Then the mean is E(X) = x*f(x) integrated with respect to x over D.
Calculate E(X2) = x2*f(x) integrated with respect to x over D.
Then Variance(X) = E(X2) - [E(X)]2
and Standard Deviation = sqrt(Variance).
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How do you generate a Gaussian bell shape graph when you have a mean and standard deviation and absolutely no other data?
The Gaussian "Bell" Curve has probability density function: f(x)= exp{-((x-mu)2/(2*sigma2)) } / (sigma*sqrt(2*pi)) where mu=mean & sigma=standard deviation
How do you convert a beta probability density function to a beta frequency distribution?
probability density distribution
What pdf stands for in statistics?
Probability Density Function
How do you find the probability density function?
The probability density function of a random variable can be either chosen from a group of widely used probability density functions (e.g.: normal, uniform, exponential), based on theoretical arguments, or estimated from the data (if you are observing data generated by a specific density function). More material on density functions can be found by following the links below.
What is the difference between a probability mass function and a probability density function?
The probability mass function is used to characterize the distribution of discrete random variables, while the probability density function is used to characterize the distribution of absolutely continuous random variables. You might want to read more about this at www.statlect.com/prbdst1.htm (see the link below or on the right)
