学术统计和数据科学合作单位的现状及实例

Pub Date : 2024-07-26 DOI:10.1002/sta4.718

Julia Sharp, Emily H. Griffith, Bruce A. Craig, Alexandra Hanlon, Sarah Peskoe, Jennifer Van Mullekom

{"title":"学术统计和数据科学合作单位的现状及实例","authors":"Julia Sharp, Emily H. Griffith, Bruce A. Craig, Alexandra Hanlon, Sarah Peskoe, Jennifer Van Mullekom","doi":"10.1002/sta4.718","DOIUrl":null,"url":null,"abstract":"The delivery of academic statistical collaboration resources can vary among types of institutions and across time. In particular, this variation might occur in the management of infrastructure and the business model, the staffing model and opportunities for staff development. In this manuscript, we present examples of these three themes in modern academic statistical collaboration units and describe key advantages and challenges.","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The current landscape of academic statistical and data science collaboration units with examples\",\"authors\":\"Julia Sharp, Emily H. Griffith, Bruce A. Craig, Alexandra Hanlon, Sarah Peskoe, Jennifer Van Mullekom\",\"doi\":\"10.1002/sta4.718\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The delivery of academic statistical collaboration resources can vary among types of institutions and across time. In particular, this variation might occur in the management of infrastructure and the business model, the staffing model and opportunities for staff development. In this manuscript, we present examples of these three themes in modern academic statistical collaboration units and describe key advantages and challenges.\",\"PeriodicalId\":0,\"journal\":{\"name\":\"\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0,\"publicationDate\":\"2024-07-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1002/sta4.718\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1002/sta4.718","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

不同类型的机构和不同时期提供的学术统计协作资源可能会有所不同。特别是在基础设施管理和业务模式、人员配置模式以及员工发展机会方面，这种差异可能会出现。在本手稿中，我们将举例说明现代学术统计合作单位的这三个主题，并介绍其主要优势和挑战。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文

The current landscape of academic statistical and data science collaboration units with examples

The delivery of academic statistical collaboration resources can vary among types of institutions and across time. In particular, this variation might occur in the management of infrastructure and the business model, the staffing model and opportunities for staff development. In this manuscript, we present examples of these three themes in modern academic statistical collaboration units and describe key advantages and challenges.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助