COEFFICIENT OF VARIATION: A NEW APPROACH FOR THE STUDY IN MAIZE EXPERIMENTS

M. Nardino, J. M. Pereira, Vinícius Torres Marques, Fabiano Costa D'avila, Francisco Dias Franco, W. S. Barros
{"title":"COEFFICIENT OF VARIATION: A NEW APPROACH FOR THE STUDY IN MAIZE EXPERIMENTS","authors":"M. Nardino, J. M. Pereira, Vinícius Torres Marques, Fabiano Costa D'avila, Francisco Dias Franco, W. S. Barros","doi":"10.28951/rbb.v38i2.440","DOIUrl":null,"url":null,"abstract":"§ ABSTRACT: The magnitude of the variation coefficient (CV) is insufficient to validate the quality of the experiment, regardless of the number of treatments, repetitions and effect of treatments. The objective was to develop a new approach to the study of coefficient of variation, as well as evaluations of these nuances with applicability in new scientific research. The study was conducted via computer simulation. The replicates (r) ranged from 2, 3, 4, 5, 10 to 20. The treatment number (t) ranged from t 5, 10, 15, 20, 25 and 30. In each of these combined scenarios we have the variation of 25 different CVs, ranging from 1, 3, 5, 7, ..., 49 to 51 %. It was imposed the variation of 11 treatment effects 0, 240, 480, 720, ..., 2000, 2400 kg ha-1, totaling 9,900.00 scenarios. The type I error is statistically invariant in the scenarios studied. With high treatment effect the CV has no implications on the power of the test (1-β). The results obtained in this research reveal that experiments with a high percentage of CV are sufficient to obtain high probabilities of the power of the F test, which do not compromise the complementary analyzes.","PeriodicalId":36293,"journal":{"name":"Revista Brasileira de Biometria","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Revista Brasileira de Biometria","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.28951/rbb.v38i2.440","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 2

Abstract

§ ABSTRACT: The magnitude of the variation coefficient (CV) is insufficient to validate the quality of the experiment, regardless of the number of treatments, repetitions and effect of treatments. The objective was to develop a new approach to the study of coefficient of variation, as well as evaluations of these nuances with applicability in new scientific research. The study was conducted via computer simulation. The replicates (r) ranged from 2, 3, 4, 5, 10 to 20. The treatment number (t) ranged from t 5, 10, 15, 20, 25 and 30. In each of these combined scenarios we have the variation of 25 different CVs, ranging from 1, 3, 5, 7, ..., 49 to 51 %. It was imposed the variation of 11 treatment effects 0, 240, 480, 720, ..., 2000, 2400 kg ha-1, totaling 9,900.00 scenarios. The type I error is statistically invariant in the scenarios studied. With high treatment effect the CV has no implications on the power of the test (1-β). The results obtained in this research reveal that experiments with a high percentage of CV are sufficient to obtain high probabilities of the power of the F test, which do not compromise the complementary analyzes.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
变异系数:玉米试验研究的新方法
§摘要:无论处理次数、重复次数和处理效果如何,变异系数(CV)的大小都不足以验证实验的质量。目的是开发一种新的方法来研究变异系数,以及评估这些细微差别,并在新的科学研究中适用。这项研究是通过计算机模拟进行的。重复数(r)为2、3、4、5、10 ~ 20。处理次数(t)为5、10、15、20、25、30次。在这些组合的场景中,我们有25种不同的cv,范围从1、3、5、7……49%至51%。施加了11种处理效应0、240、480、720、…, 2000, 2400公斤ha-1,共计9,900.00个场景。在所研究的场景中,第一类误差在统计上是不变的。在治疗效果高的情况下,CV对试验的功效没有影响(1-β)。本研究获得的结果表明,具有高CV百分比的实验足以获得F检验功率的高概率,这不会损害互补分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Revista Brasileira de Biometria
Revista Brasileira de Biometria Agricultural and Biological Sciences-Agricultural and Biological Sciences (all)
自引率
0.00%
发文量
0
审稿时长
53 weeks
期刊最新文献
CLUSTER ANALYSIS IDENTIFIES VARIABLES RELATED TO PROGNOSIS OF BREAST CANCER DISEASE UROCHLOA GRASS GROWTH AS A FUNCTION OF NITROGEN AND PHOSPHORUS FERTILIZATION BEST LINEAR UNBIASED LATENT VALUES PREDICTORS FOR FINITE POPULATION LINEAR MODELS WITH DIFFERENT ERROR SOURCES ANALYSIS OF COVID-19 CONTAMINATION AND DEATHS CASES IN BRAZIL ACCORDING TO THE NEWCOMB-BENFORD INCIDENCE AND LETHALITY OF COVID-19 CLUSTERS IN BRAZIL VIA CIRCULAR SCAN METHOD
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1