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  • 标题:Infer More, Describe Less: More Powerful Survey Conclusions through Easy Inferential Tests
  • 本地全文:下载
  • 作者:Christy Hightower ; Kerry Scott
  • 期刊名称:Issues in Science and Technology Librarianship : a quarterly publication of the Science and Technology Section, Association of College and Research Libraries
  • 电子版ISSN:1092-1206
  • 出版年度:2012
  • 期号:69
  • 页码:1-12
  • DOI:10.5062/F45H7D64
  • 出版社:Association of College and Research Libraries
  • 摘要:Many librarians use data from surveys to make decisions about how to spend money or allocate staff, often making use of popular online tools like Survey Monkey. In this era of reduced budgets, low staffing, stiff competition for new resources, and increasingly complex choices, it is especially important that librarians know how to get strong, statistically reliable direction from the survey data they depend upon. This article focuses on three metrics that are easy to master and will go a long way toward making librarians' survey conclusions more powerful and more meaningful: margin of error (MoE), confidence Level (CL), and cross-tabulation table analysis. No complex mathematics or expensive software is required: two simple and free online calculators are introduced that will do the math for you. This article puts the power of improved survey analysis within reach of every librarian and includes eight recommended best practices.
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