{"title":"After the histogram what? a description of new computer methods for estimating the population density","authors":"M. Tarter, R. L. Holcomb, Richard A. Kronman","doi":"10.1145/800196.806019","DOIUrl":null,"url":null,"abstract":"This paper has been written with two purposes in mind: First, to give a user-oriented analysis of the problem of graphical data description for univariate data and second, to describe the use of a computer program which has been designed to supplement the traditional methods. The histogram, frequency polygon and other closely related methods are computationally simple techniques, often used for estimating the underlying density of which the data are a sample. Therefore it is not at all surprising that before the advent of high speed calculation these methods were used almost exclusively. However, at the present time the criterion of simplicity is sharing the attention of statisticians and computer scientists with the criterion of efficiency in terms of effective use of data for this purpose.","PeriodicalId":257203,"journal":{"name":"Proceedings of the 1967 22nd national conference","volume":"157 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1967-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 1967 22nd national conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/800196.806019","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13
Abstract
This paper has been written with two purposes in mind: First, to give a user-oriented analysis of the problem of graphical data description for univariate data and second, to describe the use of a computer program which has been designed to supplement the traditional methods. The histogram, frequency polygon and other closely related methods are computationally simple techniques, often used for estimating the underlying density of which the data are a sample. Therefore it is not at all surprising that before the advent of high speed calculation these methods were used almost exclusively. However, at the present time the criterion of simplicity is sharing the attention of statisticians and computer scientists with the criterion of efficiency in terms of effective use of data for this purpose.