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Stably updating mean and standard deviation of data
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Communications of the ACM archive
Volume 18 ,  Issue 1  (January 1975) table of contents
Pages: 57 - 58  
Year of Publication: 1975
ISSN:0001-0782
Author
Richard J. Hanson  Washington State Univ., Pullman
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 4,   Downloads (12 Months): 45,   Citation Count: 5
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ABSTRACT

By considering the (sample) mean of a set of data as a fit to this data by a constant function, a computational method is given based on a matrix formulation and Givens transformations. The (sample) mean and standard deviation can be updated as data accumulates. The procedure is numerically stable and does not require storage of the data. Methods for dealing with weighted data and data removal are presented. When updating the mean and square of the standard deviation, the process requires no square roots.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Lawson, C.L., and Hanson, R.J. Solving least Squares Problems. Prentice-Hall, Englewood Cliffs, N.J., 1974.
 
2
Gentleman, W.M. Least squares computations by Givens transformations without square roots. J. Inst. Maths. Applies. 12 (1973), 329-336.