Practical Business Statistics, Student Solutions Manual (e-only)

Practical Business Statistics, Sixth Edition, is a conceptual, realistic, andmatter-of-fact approach to managerial statistics that carefully maintains-butdoes not overemphasize-mathematical correctness. The book offers a deepunderstanding of how to learn from data and how to deal with uncertainty whilepromoting the use of practical computer applications. This teaches present andfuture managers how to use and understand statistics without an overdose oftechnical detail, enabling them to better understand the concepts at hand andto interpret results. The text uses excellent examples with real world datarelating to the functional areas within Business such as finance, accounting,and marketing. It is well written and designed to help students gain a solidunderstanding of fundamental statistical principles without bogging them downwith excess mathematical details.

Andrew F. Siegel holds the Grant I. Butterbaugh Professorship in Quantitative Methods and Finance at the Michael G. Foster School of Business, University of Washington, Seattle, and is also Adjunct Professor in the Department of Statistics. His Ph.D. is in statistics from Stanford University (1977). Before settling in Seattle, he held teaching and/ or research positions at Harvard University, the University of Wisconsin, the RAND Corporation, the Smithsonian Institution, and Princeton University. He has taught statistics at both undergraduate and graduate levels, and earned seven teaching awards in 2015 and 2016. The interest-rate model he developed with Charles Nelson (the Nelson-Siegel Model) is in use at central banks around the world. His work has been translated into Chinese and Russian. His articles have appeared in many publications, including the Journal of the American Statistical Association, the Encyclopedia of Statistical Sciences, the American Statistician, Proceedings of the National Academy of Sciences, Nature, the American Mathematical Monthly, the Journal of the Royal Statistical Society, the Annals of Statistics, the Annals of Probability, the Society for Industrial and Applied Mathematics Journal on Scientific and Statistical Computing, Statistics in Medicine, Biometrika, Biometrics, Statistical Applications in Genetics and Molecular Biology, Mathematical Finance, Contemporary Accounting Research, the Journal of Finance, and the Journal of Applied Probability.