René's URL Explorer Experiment

Title: Variance -- from Wolfram MathWorld

Open Graph Title: Variance -- from Wolfram MathWorld

X Title: Variance -- from Wolfram MathWorld

Description: For a single variate X having a distribution P(x) with known population mean mu, the population variance var(X), commonly also written sigma^2, is defined as sigma^2=<(X-mu)^2>, (1) where mu is the population mean and denotes the expectation value of X. For a discrete distribution with N possible values of x_i, the population variance is therefore sigma^2=sum_(i=1)^NP(x_i)(x_i-mu)^2, (2) whereas for a continuous distribution, it is given by sigma^2=intP(x)(x-mu)^2dx....

Open Graph Description: For a single variate X having a distribution P(x) with known population mean mu, the population variance var(X), commonly also written sigma^2, is defined as sigma^2=<(X-mu)^2>, (1) where mu is the population mean and denotes the expectation value of X. For a discrete distribution with N possible values of x_i, the population variance is therefore sigma^2=sum_(i=1)^NP(x_i)(x_i-mu)^2, (2) whereas for a continuous distribution, it is given by sigma^2=intP(x)(x-mu)^2dx....

X Description: For a single variate X having a distribution P(x) with known population mean mu, the population variance var(X), commonly also written sigma^2, is defined as sigma^2=<(X-mu)^2>, (1) where mu is the population mean and denotes the expectation value of X. For a discrete distribution with N possible values of x_i, the population variance is therefore sigma^2=sum_(i=1)^NP(x_i)(x_i-mu)^2, (2) whereas for a continuous distribution, it is given by sigma^2=intP(x)(x-mu)^2dx....

Opengraph URL: https://mathworld.wolfram.com/Variance.html

X: @WolframResearch

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Domain: mathworld.wolfram.com

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