{"title":"Multivariate Statistical Methods in Evaluation of Concrete and Aggregate Properties","authors":"P. Hudec","doi":"10.14359/6114","DOIUrl":null,"url":null,"abstract":"Simple univariate statistical analyses such as mean, standard deviation, and bivariate regression, and correlation etc. are in widespread use in concrete technology. However, they only give results concerning at most two variables at a time. In the real world, the properties such as strength, frost resistance, alkali reactivity, etc. depend on several mutually dependent variables. For instance, multivariate statistical techniques such as cluster analysis can group all aggregates with similar properties; factor analysis can discern what combination of tests best describe a desired property of concrete, and stepwise regression analysis can be used to predict serviceability (project life) of concrete or aggregate based on several standard tests. Examples of the above statistical techniques are presented in a non-technical format, based on research into concrete aggregate properties as related to their service record.","PeriodicalId":109987,"journal":{"name":"SP-171: Third CANMET/ACI International Symposium on Advances in Concrete Technology","volume":"64 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SP-171: Third CANMET/ACI International Symposium on Advances in Concrete Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14359/6114","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Simple univariate statistical analyses such as mean, standard deviation, and bivariate regression, and correlation etc. are in widespread use in concrete technology. However, they only give results concerning at most two variables at a time. In the real world, the properties such as strength, frost resistance, alkali reactivity, etc. depend on several mutually dependent variables. For instance, multivariate statistical techniques such as cluster analysis can group all aggregates with similar properties; factor analysis can discern what combination of tests best describe a desired property of concrete, and stepwise regression analysis can be used to predict serviceability (project life) of concrete or aggregate based on several standard tests. Examples of the above statistical techniques are presented in a non-technical format, based on research into concrete aggregate properties as related to their service record.