On the basis of that study, we suggest using nonparametric charts to monitor count data when it is uncertain that the count data can be described well by a parametric distribution model.doi:10.1002/qre.2368Wang, ZhiqiongQiu, PeihuaWiley-BlackwellQuality & Reliability Engineering International
In statistics, parametric and nonparametric methodologies refer to those in which a set of data has a normal vs. a non-normal distribution, respectively. Parametric tests make certain assumptions about a data set; namely, that the data are drawn from a population with a specific (normal) distri...
It’s true that nonparametric tests don’t require data that are normally distributed. However, nonparametric tests have the disadvantage of an additional requirement that can be very hard to satisfy. The groups in a nonparametric analysis typically must all have the same variability (dispersion). ...
Parametric and nonparametric analyses of repeated ordinal categorical data. Biom J 2004;46:460- 473.Julio M Singer,,Frederico Z Poleto,and Patricia Rosa.Parametric and Nonparametric Analyses of Repeated Ordinal Categorical Data.Biometrical Journal. 2004...
Aljawadi, B. A., Abu Bakar, M. R. and Ibrahim, N. A., 2012. "Nonparametric versus Parametric Estimation of the Cure Fraction Using Interval Censored Data" Communications in statistics-Theory and Methods, 41(23).Aljawadi, B. A. I., Bakar, M. R. A. and Ibrahim, N. A. (2012)....
(1991). Dealing with nonnormal data: Parametric analysis of transformed data vs nonparametric analysis. Educational & Psychological Measurement, 51, 809-820. Raudenbush, S. W. Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods (2nd ed.). Newbury Park, ...
Parametric vs. Nonparametric VaR Thenonparametric methoddoes not require that the population being analyzed meet certain assumptions, or parameters. This gives analysts a great deal of flexibility and allows for qualitative or ordinal variables to be included. ...
Nonparametric regression is similar to linear regression, Poisson regression, and logit or probit regression; it predicts a mean of an outcome for a set of covariates. If you work with the parametric models mentioned above or other models that predict means, you already understand nonparametric regr...
Salmaso, LuigiArboretti, R.; Bathke, A.; Bonnini, S.; Bordignon, P.; Carrozzo, E.; Corain, L.; Salmaso, L. Parametric and Nonparametric Statistics for Sample Surveys and Customer Satisfaction Data; Springer: Cham, Switzerland, 2018....
This required number of lever presses provided the PR requirement at the indifference point of the session data. Statistical significance among four parameter pairs was first tested with the two-factor nonparametric Scheirer-Ray-Hare test and the post-hoc pairwise comparison was done with Rank-sum ...