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The Future of Statistical Software: Proceedings of a Forum Morning Session Opening Remarks Barbara Ryan Minitab, Inc. The question faced by the Panel on Guidelines for Statistical Software is how to provide effective guidance to people involved with statistical software. The audience we are trying to address consists of people who have to review software for one reason or another--for their own personal use, for use within a company or a university, or perhaps for presentation in a trade publication, professional journal, or popular magazine. We want to address people who are trying to understand statistical software, recognize good software, and know how to look at software to assess whether it will meet their needs. Another group we expect the report to influence is the vendors who produce software. We want the vendors to produce the best possible software for the users. In the late 1970s, when the American Statistical Association got involved in evaluating statistical software, there was some concern from the vendor community about how that was done. But it had one major effect: it improved the quality of statistical software. Very few vendors wanted to appear to be uninformed, and so they made sure their software met some of the criteria that the statisticians considered very important. Our panel hopes that its future report, to which this forum will provide input, will also influence vendors to improve their products in ways that will help people to do statistical work well. The panel has identified three qualities of statistical software as important: richness, exactness, and guidance. Although others are also important, these were selected as a means to structure the panel's efforts. Richness will be emphasized this morning and guidance will be featured this afternoon; exactness will arise throughout the day as appropriate. By richness, we mean: What does the software do, what type of analysis? Does it have depth? Does it have breadth? Those qualities are not necessarily always good things. For some people, too much depth and too much breadth are confusing. So richness is not automatically a good quality, but it is an important quality.
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The Future of Statistical Software: Proceedings of a Forum This page in the original is blank.
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