Transformation of Data for Statistical Processing
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příspěvek z konference - elektronickýAuthor
Mach, Pavel
Thuring, Josef
Šámal, David
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© 2006 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Metadata
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The use of many statistical tools depends on normality of processed data. There are different methods for transformation of non-normally distributed data sets toward to normally distributed ones. The goal of the work has been to investigate usability of four types of transformations (Box-Cox, exponential, power and logarithmic) for transformation of data sets with four non-normal distributions (logarithmic-normal, exponential, gamma, and Weibull) toward to normally distributed data. The usability and efficiency of individual transformation functions for transformation of data sets with different types of distributions have been found.
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