Add to ORKGParametric statistical procedures are based on certain assumptions. For example, the assumption that samples have been drawn from normally distributed populations. Since real life populations do not always meet the assumptions underlying parametric tests, we need some procedures whose validity do not depend on rigid assumptions. In this way
Despite forty years of revolution in the tools available for statistical analysis, the current acade...
International audienceAbstractThere are famous examples of acute sensitivity of optimal parametric p...
We outline how modern likelihood theory, which provides essentially exact inferences in a variety of...
center, shape and spread and described how the validity of many statistical procedures relies on an ...
The use of parametric procedures similar to those nonparametric ones introduced in the paper "Nonpar...
A parametric test specifies certain conditions about the distribution of responses in the populatio...
Classical parametric methods of statistical inference and hypothesis testing are derived under funda...
Many statistical tests are based around an assumption of “normality”. The reasoning for this choice...
Classical statistical inference relies mostly on parametric models and on optimal procedures which a...
Classical statistical inference methods (parametric methods) have a common denominator, i.e. a popul...
One of the assumptions for most parametric tests to be reliable is that the data is approximately no...
Introduction: Application of statistical software typically does not require extensive statistical k...
Most statistical methods require assumptions about the populations from which samples are taken. Usu...
The parametric tests are often used as default without regard to distribution shape. Even more rarel...
Often scientific information on various data generating processes are presented in the from of numer...
Despite forty years of revolution in the tools available for statistical analysis, the current acade...
International audienceAbstractThere are famous examples of acute sensitivity of optimal parametric p...
We outline how modern likelihood theory, which provides essentially exact inferences in a variety of...
center, shape and spread and described how the validity of many statistical procedures relies on an ...
The use of parametric procedures similar to those nonparametric ones introduced in the paper "Nonpar...
A parametric test specifies certain conditions about the distribution of responses in the populatio...
Classical parametric methods of statistical inference and hypothesis testing are derived under funda...
Many statistical tests are based around an assumption of “normality”. The reasoning for this choice...
Classical statistical inference relies mostly on parametric models and on optimal procedures which a...
Classical statistical inference methods (parametric methods) have a common denominator, i.e. a popul...
One of the assumptions for most parametric tests to be reliable is that the data is approximately no...
Introduction: Application of statistical software typically does not require extensive statistical k...
Most statistical methods require assumptions about the populations from which samples are taken. Usu...
The parametric tests are often used as default without regard to distribution shape. Even more rarel...
Often scientific information on various data generating processes are presented in the from of numer...
Despite forty years of revolution in the tools available for statistical analysis, the current acade...
International audienceAbstractThere are famous examples of acute sensitivity of optimal parametric p...
We outline how modern likelihood theory, which provides essentially exact inferences in a variety of...