{"title":"离散数据线性回归的应用","authors":"S. Jozová, I. Nagy","doi":"10.1109/SCSP52043.2021.9447393","DOIUrl":null,"url":null,"abstract":"Data analysis is very important tool for acquiring information about object of our interest. It involves a lot of various methods, mainly from the area of data mining or statistical analysis. However, most of these methods aim at continuous data. In real applications, especially in the field of Smart Cities, questionnaires are a frequent source of data. They are mainly a source of discrete data. As commonly used data analysis methods, such as regression analysis, naturally work with continuous data, complications can occur. However, the linear regression analysis can be carefully used to to analyze discrete data, but carefully.The paper wants to give a warning before a direct mindless use of regression analysis for discrete data, especially when the independent variables are nominal. Also some ways how to modify values of the independent variables to achieve sensible results with linear regression applied to measured discrete data from the Smart City area are sketched.","PeriodicalId":158827,"journal":{"name":"2021 Smart City Symposium Prague (SCSP)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Use of Linear Regression to Discrete Data\",\"authors\":\"S. Jozová, I. Nagy\",\"doi\":\"10.1109/SCSP52043.2021.9447393\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Data analysis is very important tool for acquiring information about object of our interest. It involves a lot of various methods, mainly from the area of data mining or statistical analysis. However, most of these methods aim at continuous data. In real applications, especially in the field of Smart Cities, questionnaires are a frequent source of data. They are mainly a source of discrete data. As commonly used data analysis methods, such as regression analysis, naturally work with continuous data, complications can occur. However, the linear regression analysis can be carefully used to to analyze discrete data, but carefully.The paper wants to give a warning before a direct mindless use of regression analysis for discrete data, especially when the independent variables are nominal. Also some ways how to modify values of the independent variables to achieve sensible results with linear regression applied to measured discrete data from the Smart City area are sketched.\",\"PeriodicalId\":158827,\"journal\":{\"name\":\"2021 Smart City Symposium Prague (SCSP)\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-05-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 Smart City Symposium Prague (SCSP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SCSP52043.2021.9447393\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 Smart City Symposium Prague (SCSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SCSP52043.2021.9447393","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Data analysis is very important tool for acquiring information about object of our interest. It involves a lot of various methods, mainly from the area of data mining or statistical analysis. However, most of these methods aim at continuous data. In real applications, especially in the field of Smart Cities, questionnaires are a frequent source of data. They are mainly a source of discrete data. As commonly used data analysis methods, such as regression analysis, naturally work with continuous data, complications can occur. However, the linear regression analysis can be carefully used to to analyze discrete data, but carefully.The paper wants to give a warning before a direct mindless use of regression analysis for discrete data, especially when the independent variables are nominal. Also some ways how to modify values of the independent variables to achieve sensible results with linear regression applied to measured discrete data from the Smart City area are sketched.