The Web sites that academic libraries are developing for their research communities represent an important new aspect of information management. Comparative statistical analysis of Web site usage among similar institutions would improve librarians’ ability to evaluate the effectiveness of their efforts. A centralized voluntary reporting structure for Web server usage statistics, coordinated by the Association of Research Libraries’ (ARL’s) Office of Statistics, would provide a significant service to academic librarians. Factors to consider in designing such a benchmarking program are discussed, based on a pilot study of Web site usage statistics from fourteen science and technology libraries.

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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. [ABSTRACT FROM AUTHOR]

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