Focuses on underlying principles that are important to students in a range of disciplines. This book emphasizes the interpretation of results, the presentation and evaluation of assumptions, and the discussion of what should be done if the assumptions are violated. It is appropriate for courses in Probability and Statistics.
Focuses on underlying principles that are important to students in a range of disciplines. This book emphasizes the interpretation of results, the presentation and evaluation of assumptions, and the discussion of what should be done if the assumptions are violated. It is appropriate for courses in Probability and Statistics.
For courses in Probability and Statistics. This applied text for engineers and scientists, written in a non-theoretical manner, focuses on underlying principles that are important to students in a wide range of disciplines. It emphasizes the interpretation of results, the presentation and evaluation of assumptions, and the discussion of what should be done if the assumptions are violated. Integration of spreadsheet and statistical software (Microsoft Excel and Minitab) as well as in-depth coverage of quality and experimental design complete this treatment of statistics.
David M. Levine is one of the world's leading innovators in statistics education. He is Professor Emeritus of Statistics and Computer Information Systems at Bernard M. Baruch College (CUNY), and co-author of several best-selling books, including "Statistics for Managers using Microsoft Excel, Quality Management," and "Six Sigma for Green Belts and Champions,"
Instructional designer David F. Stephan pioneered the classroom use of technology, and is a leader in making Excel more accessible to statistics students. He has co-authored several textbooks with David M. Levine.
For courses in Probability and Statistics. This applied text for engineers and scientists, written in a non-theoretical manner, focuses on underlying principles that are important to students in a wide range of disciplines. It emphasizes the interpretation of results, the presentation and evaluation of assumptions, and the discussion of what should be done if the assumptions are violated. Integration of spreadsheet and statistical software (Microsoft Excel and Minitab) as well as in-depth coverage of quality and experimental design complete this treatment of statistics.
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