{"title":"数据管理与跨文化描述性分析","authors":"T. Tran, Keith T Chan","doi":"10.1093/oso/9780190888510.003.0003","DOIUrl":null,"url":null,"abstract":"Quantitative cross-cultural analysis requires the application of statistics to study the variability of a phenomenon (variable,) across cultural groups. This chapter aims to provide practical applications of descriptive statistics to describe the variables used in a cross-cultural research/evaluation project. We use statistical methods to describe the variables of interests and to test the hypotheses derived from theories for understanding cross-cultural comparisons. More specifically, we address the importance of examine the variables of interest across selected comparative groups. It is our position that in order to describe and to test hypotheses, we need first to know how the variables of interest are measured. We illustrate the use of STATA for data management and descriptive statistics throughout the chapter.","PeriodicalId":415847,"journal":{"name":"Applied Cross-Cultural Data Analysis for Social Work","volume":"142 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Data Management and Cross-Cultural Descriptive Analysis\",\"authors\":\"T. Tran, Keith T Chan\",\"doi\":\"10.1093/oso/9780190888510.003.0003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Quantitative cross-cultural analysis requires the application of statistics to study the variability of a phenomenon (variable,) across cultural groups. This chapter aims to provide practical applications of descriptive statistics to describe the variables used in a cross-cultural research/evaluation project. We use statistical methods to describe the variables of interests and to test the hypotheses derived from theories for understanding cross-cultural comparisons. More specifically, we address the importance of examine the variables of interest across selected comparative groups. It is our position that in order to describe and to test hypotheses, we need first to know how the variables of interest are measured. We illustrate the use of STATA for data management and descriptive statistics throughout the chapter.\",\"PeriodicalId\":415847,\"journal\":{\"name\":\"Applied Cross-Cultural Data Analysis for Social Work\",\"volume\":\"142 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Cross-Cultural Data Analysis for Social Work\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/oso/9780190888510.003.0003\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Cross-Cultural Data Analysis for Social Work","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/oso/9780190888510.003.0003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Data Management and Cross-Cultural Descriptive Analysis
Quantitative cross-cultural analysis requires the application of statistics to study the variability of a phenomenon (variable,) across cultural groups. This chapter aims to provide practical applications of descriptive statistics to describe the variables used in a cross-cultural research/evaluation project. We use statistical methods to describe the variables of interests and to test the hypotheses derived from theories for understanding cross-cultural comparisons. More specifically, we address the importance of examine the variables of interest across selected comparative groups. It is our position that in order to describe and to test hypotheses, we need first to know how the variables of interest are measured. We illustrate the use of STATA for data management and descriptive statistics throughout the chapter.