{"title":"拟合优度和独立性测试:测试分布。","authors":"A. Kozak, R. Kozak, C. Staudhammer, S. B. Watts","doi":"10.1079/9781845932756.0201","DOIUrl":null,"url":null,"abstract":"Abstract\n This chapter introduces tests concerning distributions of one or more populations by using data from a large sawmill. The goodness-of-fit test is used to determine whether a population follows a specified theoretical distribution, and the test for independence (or a contingency table) is used to compare two or more distributions.","PeriodicalId":413890,"journal":{"name":"Introductory probability and statistics: applications for forestry and natural sciences","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Goodness-of-fit and test for independence: testing distributions.\",\"authors\":\"A. Kozak, R. Kozak, C. Staudhammer, S. B. Watts\",\"doi\":\"10.1079/9781845932756.0201\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract\\n This chapter introduces tests concerning distributions of one or more populations by using data from a large sawmill. The goodness-of-fit test is used to determine whether a population follows a specified theoretical distribution, and the test for independence (or a contingency table) is used to compare two or more distributions.\",\"PeriodicalId\":413890,\"journal\":{\"name\":\"Introductory probability and statistics: applications for forestry and natural sciences\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Introductory probability and statistics: applications for forestry and natural sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1079/9781845932756.0201\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Introductory probability and statistics: applications for forestry and natural sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1079/9781845932756.0201","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Goodness-of-fit and test for independence: testing distributions.
Abstract
This chapter introduces tests concerning distributions of one or more populations by using data from a large sawmill. The goodness-of-fit test is used to determine whether a population follows a specified theoretical distribution, and the test for independence (or a contingency table) is used to compare two or more distributions.