Book by Hogg Robert V Ledolter Johannes
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Johannes Ledolter is a Professor of Statistics and Actuarial Sciences at the University of Iowa as well as a C. Maxwell Stanley Professor of International Operations Management at the Henry B. Tippie College of Business. Ledolter received his M.S. and Ph.D. degrees in Statistics from the University of Wisconsin-Madison along with an M.S degree in Social and Economic Statistics from the University of Vienna. His research interests are in time series analysis, forecasting, and applied statistical modeling. His publications have appeared in Biometrika, Technometrics, Communications in Statistics, and Management Science. He is the co-author of several books including Experimental Design with Applications in Marketing and Service Operations, Introduction to Regression Modeling, Statistical Quality Control, andStatistical Methods for Forecasting.
Robert V. Hogg, Professor Emeritus of Statistics at the University of Iowa since 2001, received his B.A. in mathematics at the University of Illinois and his M.S. and Ph.D. degrees in mathematics, specializing in actuarial sciences and statistics, from the University of Iowa. Known for his gift of humor and his passion for teaching, Hogg has had far-reaching influence in the field of statistics. Throughout his career, Hogg has played a major role in defining statistics as a unique academic field, and he almost literally "wrote the book" on the subject. He has written more than 70 research articles and co-authored four books including Introduction of Mathematical Statistics, 6th edition, with J. W. McKean and A.T. Craig, as well as Probability and Statistical Inference, 8th edition and A Brief Course in Mathematical 1st edition, both with E.A. Tanis. His texts have become classroom standards used by hundreds of thousands of students
Among the many awards he has received for distinction in teaching, Hogg has been honored at the national level (the Mathematical Association of America Award for Distinguished Teaching), the state level (the Governor's Science Medal for Teaching), and the university level (Collegiate Teaching Award). His important contributions to statistical research have been acknowledged by his election to fellowship standing in the ASA and the Institute of Mathematical Statistics.
This hugely anticipated revision has held true to its core strengths, while bringing the book fully up to date with modern engineering statistics. Written by two leading statisticians, Statistics for Engineers and Physical Scientists, Third Edition, provides the necessary bridge between basic statistical theory and interesting applications. Students solve the same problems that engineers and scientists face, and have the opportunity to analyze real data sets. Larger-scale projects are a unique feature of this book, which let students analyze and interpret real data, while also encouraging them to conduct their own studies and compare approaches and results.
This book assumes a calculus background. It is appropriate for undergraduate and graduate engineering or physical science courses or for students taking an introductory course applied statistics.
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