抛弃常规:使用替代分布进行生物数据分析

IF 1.3 4区 农林科学 Q2 VETERINARY SCIENCES
Laboratory Animals Pub Date : 2024-10-01 Epub Date: 2024-08-19 DOI:10.1177/00236772241246602
Stanley E Lazic
{"title":"抛弃常规:使用替代分布进行生物数据分析","authors":"Stanley E Lazic","doi":"10.1177/00236772241246602","DOIUrl":null,"url":null,"abstract":"<p><p>Most classical statistical tests assume data are normally distributed. If this assumption is not met, researchers often turn to non-parametric methods. These methods have some drawbacks, and if no suitable non-parametric test exists, a normal distribution may be used inappropriately instead. A better option is to select a distribution appropriate for the data from dozens available in modern software packages. Selecting a distribution that represents the data generating process is a crucial but overlooked step in analysing data. This paper discusses several alternative distributions and the types of data that they are suitable for.</p>","PeriodicalId":18013,"journal":{"name":"Laboratory Animals","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Ditching the norm: Using alternative distributions for biological data analysis.\",\"authors\":\"Stanley E Lazic\",\"doi\":\"10.1177/00236772241246602\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Most classical statistical tests assume data are normally distributed. If this assumption is not met, researchers often turn to non-parametric methods. These methods have some drawbacks, and if no suitable non-parametric test exists, a normal distribution may be used inappropriately instead. A better option is to select a distribution appropriate for the data from dozens available in modern software packages. Selecting a distribution that represents the data generating process is a crucial but overlooked step in analysing data. This paper discusses several alternative distributions and the types of data that they are suitable for.</p>\",\"PeriodicalId\":18013,\"journal\":{\"name\":\"Laboratory Animals\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Laboratory Animals\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1177/00236772241246602\",\"RegionNum\":4,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/8/19 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"VETERINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Laboratory Animals","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/00236772241246602","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/8/19 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"VETERINARY SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

大多数经典统计检验都假设数据呈正态分布。如果不符合这一假设,研究人员通常会求助于非参数方法。这些方法有一些缺点,如果没有合适的非参数检验方法,可能会不恰当地使用正态分布。更好的选择是从现代软件包中的几十种分布中选择适合数据的分布。选择一个能代表数据生成过程的分布是分析数据的关键步骤,但却被忽视了。本文将讨论几种可供选择的分布及其适用的数据类型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ditching the norm: Using alternative distributions for biological data analysis.

Most classical statistical tests assume data are normally distributed. If this assumption is not met, researchers often turn to non-parametric methods. These methods have some drawbacks, and if no suitable non-parametric test exists, a normal distribution may be used inappropriately instead. A better option is to select a distribution appropriate for the data from dozens available in modern software packages. Selecting a distribution that represents the data generating process is a crucial but overlooked step in analysing data. This paper discusses several alternative distributions and the types of data that they are suitable for.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Laboratory Animals
Laboratory Animals 生物-动物学
CiteScore
4.90
自引率
8.30%
发文量
64
审稿时长
6-12 weeks
期刊介绍: The international journal of laboratory animal science and welfare, Laboratory Animals publishes peer-reviewed original papers and reviews on all aspects of the use of animals in biomedical research. The journal promotes improvements in the welfare or well-being of the animals used, it particularly focuses on research that reduces the number of animals used or which replaces animal models with in vitro alternatives.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信