Paulo Rogério Alves Brene, U. A. S. Filho, Rodrigo Mariano, R. Rangel
{"title":"ANÁLISE MULTIVARIADA DO SETOR SUPERMERCADISTA A PARTIR DOS DADOS DO RANKING ABRAS DO ESTADO DE SÃO PAULO (2010)","authors":"Paulo Rogério Alves Brene, U. A. S. Filho, Rodrigo Mariano, R. Rangel","doi":"10.21710/RCH.V10I0.126","DOIUrl":null,"url":null,"abstract":"The objective of this paper is to propose a methodology to illustrate the applicability and importance of multivariate analysis. To do that, it is used the data set presented on ABRAS of São Paulo for the year 2010. Thus, new indicators were developed with the aid of factor analysis (FA), 14 condensed information extracted from ABRAS on 2 factors: Size and Efficiency. As a result, it was observed that the application of AF was successful because it reduced the number of variables without losing much information, as well as showing consistency in this grouping beyond the grouping of variables. Finally, there is a direct relationship between billing classification and classification by revenue size (Spearman","PeriodicalId":41143,"journal":{"name":"Revista Cientifica Hermes","volume":"10 1","pages":""},"PeriodicalIF":0.1000,"publicationDate":"2014-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Revista Cientifica Hermes","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21710/RCH.V10I0.126","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"SOCIAL SCIENCES, INTERDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
The objective of this paper is to propose a methodology to illustrate the applicability and importance of multivariate analysis. To do that, it is used the data set presented on ABRAS of São Paulo for the year 2010. Thus, new indicators were developed with the aid of factor analysis (FA), 14 condensed information extracted from ABRAS on 2 factors: Size and Efficiency. As a result, it was observed that the application of AF was successful because it reduced the number of variables without losing much information, as well as showing consistency in this grouping beyond the grouping of variables. Finally, there is a direct relationship between billing classification and classification by revenue size (Spearman