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Elementary Statistics Using JMP

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Elementary Statistics Using JMP, 9781599943756 (1599943751), SAS Institute, 2007
Learn how to perform basic statistical analyses using the powerful JMP software. This reader-friendly guide bridges the gap between statistics texts and JMP documentation. Author Sandra Schlotzhauer opens with an explanation of the basics of JMP data tables, demonstrating how to use JMP for descriptive statistics and graphs. The author continues with a lucid discussion of fundamental statistical concepts, including normality and hypothesis testing. Using a step-by-step approach, she shows analyses for comparing two groups, comparing multiple groups, fitting regression equations, and exploring contingency tables. For each analysis, the author clearly explains assumptions, the statistical approach, the JMP steps and results, and how to make conclusions from the results.

Understand how to interpret both the graphs and text reports, as well as how to customize JMP results to meet your needs. Packed with examples from a broad range of industries, this text is ideal for novice to intermediate JMP users. Prior statistical knowledge, JMP experience, or programming skills are not required.

Includes a free CD-ROM with the example data sets and JMP tips.

About the Author

Sandra Schlotzhauer provides consulting and training services, focusing on the biopharmaceutical industry. She started Schlotzhauer Consulting LLC after 15 years of experience in the software, pharmaceutical, and aerospace industries. Sandra received her B.S. and M.S. degrees in Statistics from the University of Florida, where she learned the value of combining statistics and software. Her consulting projects share a common theme of translating technical concepts to business deliverables. She develops custom JMP courses using client data, and teaches client-developed courses. In this book, Sandra draws on her extensive experience in teaching basic statistics to non-statisticians, with a focus on using statistical methods and software as tools to make practical conclusions based on data. Sandra is also the coauthor of SAS(r) System for Elementary Statistical Analysis.

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