Title: Sample Variance Computation -- from Wolfram MathWorld
Open Graph Title: Sample Variance Computation -- from Wolfram MathWorld
X Title: Sample Variance Computation -- from Wolfram MathWorld
Description: When computing the sample variance s numerically, the mean must be computed before s^2 can be determined. This requires storing the set of sample values. However, it is possible to calculate s^2 using a recursion relationship involving only the last sample as follows. This means mu itself need not be precomputed, and only a running set of values need be stored at each step. In the following, use the somewhat less than optimal notation mu_j to denote mu calculated from the first j samples...
Open Graph Description: When computing the sample variance s numerically, the mean must be computed before s^2 can be determined. This requires storing the set of sample values. However, it is possible to calculate s^2 using a recursion relationship involving only the last sample as follows. This means mu itself need not be precomputed, and only a running set of values need be stored at each step. In the following, use the somewhat less than optimal notation mu_j to denote mu calculated from the first j samples...
X Description: When computing the sample variance s numerically, the mean must be computed before s^2 can be determined. This requires storing the set of sample values. However, it is possible to calculate s^2 using a recursion relationship involving only the last sample as follows. This means mu itself need not be precomputed, and only a running set of values need be stored at each step. In the following, use the somewhat less than optimal notation mu_j to denote mu calculated from the first j samples...
Opengraph URL: https://mathworld.wolfram.com/SampleVarianceComputation.html
Domain: mathworld.wolfram.com
| DC.Title | Sample Variance Computation |
| DC.Creator | Weisstein, Eric W. |
| DC.Description | When computing the sample variance s numerically, the mean must be computed before s^2 can be determined. This requires storing the set of sample values. However, it is possible to calculate s^2 using a recursion relationship involving only the last sample as follows. This means mu itself need not be precomputed, and only a running set of values need be stored at each step. In the following, use the somewhat less than optimal notation mu_j to denote mu calculated from the first j samples... |
| DC.Date.Created | 2003-05-06 |
| DC.Subject | 62M05 |
| DC.Rights | Copyright 1999-2026 Wolfram Research, Inc. See https://mathworld.wolfram.com/about/terms.html for a full terms of use statement. |
| DC.Format | text/html |
| DC.Identifier | https://mathworld.wolfram.com/SampleVarianceComputation.html |
| DC.Language | en |
| DC.Publisher | Wolfram Research, Inc. |
| DC.Relation.IsPartOf | https://mathworld.wolfram.com/ |
| DC.Type | Text |
| Last-Modified | 2003-05-06 |
| og:image | https://mathworld.wolfram.com/images/socialmedia/share/ogimage_SampleVarianceComputation.png |
| og:type | website |
| twitter:card | summary_large_image |
| twitter:image:src | https://mathworld.wolfram.com/images/socialmedia/share/ogimage_SampleVarianceComputation.png |
| None | ie=edge |
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