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Title: Sample Variance -- from Wolfram MathWorld

Open Graph Title: Sample Variance -- from Wolfram MathWorld

X Title: Sample Variance -- from Wolfram MathWorld

Description: The sample variance m_2 (commonly written s^2 or sometimes s_N^2) is the second sample central moment and is defined by m_2=1/Nsum_(i=1)^N(x_i-m)^2, (1) where m=x^_ the sample mean and N is the sample size. To estimate the population variance mu_2=sigma^2 from a sample of N elements with a priori unknown mean (i.e., the mean is estimated from the sample itself), we need an unbiased estimator mu^^_2 for mu_2. This estimator is given by k-statistic k_2, which is defined by ...

Open Graph Description: The sample variance m_2 (commonly written s^2 or sometimes s_N^2) is the second sample central moment and is defined by m_2=1/Nsum_(i=1)^N(x_i-m)^2, (1) where m=x^_ the sample mean and N is the sample size. To estimate the population variance mu_2=sigma^2 from a sample of N elements with a priori unknown mean (i.e., the mean is estimated from the sample itself), we need an unbiased estimator mu^^_2 for mu_2. This estimator is given by k-statistic k_2, which is defined by ...

X Description: The sample variance m_2 (commonly written s^2 or sometimes s_N^2) is the second sample central moment and is defined by m_2=1/Nsum_(i=1)^N(x_i-m)^2, (1) where m=x^_ the sample mean and N is the sample size. To estimate the population variance mu_2=sigma^2 from a sample of N elements with a priori unknown mean (i.e., the mean is estimated from the sample itself), we need an unbiased estimator mu^^_2 for mu_2. This estimator is given by k-statistic k_2, which is defined by ...

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

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Domain: mathworld.wolfram.com

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