{"title":"非正态分布连续数据的参数检验:正反","authors":"Umesh Wadgave, M. Khairnar","doi":"10.19082/7468","DOIUrl":null,"url":null,"abstract":"Choosing between parametric and non-parametric statistical tests for analysis of non-normally distributed continuous data is a long-standing controversy. Conventionally, it is recommended to use non-parametric tests but few others suggest using the parametric test. This article evaluates the simulation studies comparing the parametric tests with non-parametric tests in analysing the non-normally distributed continuous data. Nonparametric tests are recommended only when data is highly skewed and log transformation technique cannot change it to normal distribution. However, in most other situations parametric tests are more powerful in analysing non-normally distributed continuous data.","PeriodicalId":11603,"journal":{"name":"Electronic Physician","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Parametric test for non-normally distributed continuous data: For and against\",\"authors\":\"Umesh Wadgave, M. Khairnar\",\"doi\":\"10.19082/7468\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Choosing between parametric and non-parametric statistical tests for analysis of non-normally distributed continuous data is a long-standing controversy. Conventionally, it is recommended to use non-parametric tests but few others suggest using the parametric test. This article evaluates the simulation studies comparing the parametric tests with non-parametric tests in analysing the non-normally distributed continuous data. Nonparametric tests are recommended only when data is highly skewed and log transformation technique cannot change it to normal distribution. However, in most other situations parametric tests are more powerful in analysing non-normally distributed continuous data.\",\"PeriodicalId\":11603,\"journal\":{\"name\":\"Electronic Physician\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-02-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Electronic Physician\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.19082/7468\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electronic Physician","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.19082/7468","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Parametric test for non-normally distributed continuous data: For and against
Choosing between parametric and non-parametric statistical tests for analysis of non-normally distributed continuous data is a long-standing controversy. Conventionally, it is recommended to use non-parametric tests but few others suggest using the parametric test. This article evaluates the simulation studies comparing the parametric tests with non-parametric tests in analysing the non-normally distributed continuous data. Nonparametric tests are recommended only when data is highly skewed and log transformation technique cannot change it to normal distribution. However, in most other situations parametric tests are more powerful in analysing non-normally distributed continuous data.