{"title":"Proposed Procedure for Estimating the Coefficient of Three-factor Interaction for 2^p 3^m 4^q Factorial Experiments (TECHNICAL NOTE)","authors":"W. A. A. Alqraghuli, A. Alkarkhi, Y. Yusup","doi":"10.5829/ije.2018.31.01a.02","DOIUrl":null,"url":null,"abstract":"Three-factor interaction for the two-level, three-level, and four-level factorial designs was studied. A new technique and formula based on the coefficients of orthogonal polynomial contrast were proposed to calculate the effect of the three-factor interaction The results show that the proposed technique was in agreement with the least squares method. The advantages of the new technique are 1) it is fixed, 2) it is simple and 3) it is easy to apply without the complicated matrix formula of the least squares method. This new technique will also enhance the use of the coefficients of orthogonal contrast when analyzing other experimental designs.","PeriodicalId":416886,"journal":{"name":"International journal of engineering. Transactions A: basics","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of engineering. Transactions A: basics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5829/ije.2018.31.01a.02","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Three-factor interaction for the two-level, three-level, and four-level factorial designs was studied. A new technique and formula based on the coefficients of orthogonal polynomial contrast were proposed to calculate the effect of the three-factor interaction The results show that the proposed technique was in agreement with the least squares method. The advantages of the new technique are 1) it is fixed, 2) it is simple and 3) it is easy to apply without the complicated matrix formula of the least squares method. This new technique will also enhance the use of the coefficients of orthogonal contrast when analyzing other experimental designs.