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...ifically chosen either to simplify considerations in graphical exploratory data analysis or to allow the application of simple regression-based or [[analys ...variance varies with the mean. However, if the simple variance-stabilizing transformation ...

...oi-access=}}</ref><ref>{{cite journal | last=Ramsay | first=J.O. | journal=Statistical Science | year = 1988 | volume=3 | pages=425&ndash;441 | title = Monotone R ...plines for regression analysis and [[data transformation (statistics)|data transformation]] when monotonicity is desired (constraining the regression coefficients to ...

{{Short description|Data transformation of statistics into rank}} ...]] or [[Ordinal scale|ordinal]] values are replaced by their rank when the data are sorted. ...

...isplay both large magnitude [[Fold change|fold-changes]] (x axis) and high statistical significance (-log₁₀ of p value, y axis). The dashed red line sh ...-points (genes, etc.) that display large magnitude changes that are also [[Statistical significance|statistically significant]]. ...

{{Short description|Statistical property quantifying how much a collection of data is spread out}} ...ta is widely scattered. On the other hand, when the variance is small, the data in the set is clustered. ...

...ses according to a given [[metric (mathematics)|distance metric]] over the data. Functionally, it serves the same purposes as the [[K-nearest neighbors alg ...ight to the algorithm is that a matrix <math>A</math> corresponding to the transformation can be found by defining a differentiable objective function for <math>A</m ...

...Repeated Median Regression Estimator]", in ''New Directions in Statistical Data Analysis and Robustness'', edited by Stephan Morgenthaler, Elvezio Ronchett [[Category:Statistical algorithms]] ...

The '''Iman-Conover''' ('''IC''') method or transformation is a [[statistics|statistical]] method for generating a sample with a specified rank-correlation.<ref nam ...data and a target correlation matrix. The method works by rearranging the data to achieve a rank correlation close to the target correlation matrix. ...

...que for making two [[probability distribution|distributions]] identical in statistical properties. To quantile-normalize a test distribution to a reference distr Generally a reference distribution will be one of the standard statistical distributions such as the [[Gaussian distribution]] or the [[Poisson distri ...

...so known as [[data normalization]] and is generally performed during the [[data preprocessing]] step. ...without [[Normalization (statistics)|normalization]]. For example, many [[Statistical classification|classifiers]] calculate the distance between two points by t ...

In [[statistics]], a nonlinear transformation of variables is commonly used in practice in regression problems. ACE is on ...lained]]. The transformation is nonlinear and is iteratively obtained from data. ...

...ng component independence|measure]] of [[Independence (probability theory)|statistical independence]]. .../math> is a [[Whitening transformation#Whitening a data matrix|prewhitened data matrix]], that is, the sample mean of each column is zero and the sample co ...

|publisher = American Statistical Association #The influences of individual data values on the estimation of a coefficient are easy to see in this plot. ...

.../research/tech-reports/nonparametric-modelling-hierarchically-exchangeable-data Link]</ref><ref>{{cite web|url=http://brenocon.com/blog/2011/05/log-normal- ...d one. An alternative is to use the observation that the logit-normal is a transformation of a normal random variable. This allows us to approximate the <math>n</mat ...

{{Short description|Statistical field}} ...for density functions in Bayes spaces |journal=Computational Statistics & Data Analysis |via=Elsevie Science Direct}}</ref><ref>{{Cite journal |last=Talsk ...

{{Short description|Statistical model extension}} ...r and Yao|title=Functional Additive Models|journal=Journal of the American Statistical Association|year=2008|volume=103|issue=484|pages=1534–1544|doi= 10.1198/016 ...

...ntervals, making it distinctively useful in fields that deal with discrete data patterns and reliability analysis. The discrete Weibull distribution is [[I ==Location-scale transformation== ...

{{Short description|Algorithm for analyzing noisy data streams}} ...) is a [[mathematical algorithm]] that extracts useful data from a [[noisy data]] stream. ...

..." difference between two proportions is understood to mean that, given the data, it is likely that there is a difference in the population proportions. How ...umb]] criteria set out by Cohen.<ref name="Cohen 1988">{{cite book | title=Statistical Power Analysis for the Behavioral Sciences | author=Cohen, Jacob | year=198 ...

{{Short description|Statistical proof by contradiction technique}} '''Surrogate data testing'''<ref name=Theiler1> ...