Numerical Methods For Scientists and Engineers
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This well-received book, now in its second edition, is designed for an introductory course in statistics for students of statistics, mathematics and management. In addition, postgraduate students of a variety of disciplines such as psychology, sociology, anthropology, biology, nursing and criminal justice, as well as professionals, surveyors and administrators will also find this book extremely helpful.
The book provides students with a strong foundation in the principles of statistics. It develops a thorough understanding of the fundamental concepts through extensive use of illustrative and motivating examples and shows how these concepts can be applied to real-life situations.
The text explains each statistical technique and formula in a step-by-step manner with the help of small datasets. While discussing a wide range of topics, mathematical complexity has been kept at a bare minimum, and intuitive ideas have been given for each mathematical expression. Key concepts have been highlighted in boxes throughout the text. Chapter-end summaries in the form of flowchart capture all the important points. Chapter-end exercises with answers and the Question Bank containing about 150 questions offer the students the opportunity to test their ability to comprehend the concepts. Besides, this text illustrates the use of SPSS and Excel in carrying out statistical analysis.
Provides a new section on ‘Testing Normality’ of a given a dataset.
Expands Use of Technology sections with coverage of the use of Excel to perform statistical analysis.
Offers a new appendix containing Multiple-Choice Questions as brain-teasers.
Includes Excel example datasets, SPSS datasets, and the solutions to Question Bank on the companion CD.
Solutions Manual containing the complete worked-out solutions to chapter-end exercises and Question Bank is available for instructors.
SAHADEB SARKAR (Ph.D., Statistics, Iowa State University) is Professor of Statistics in the Operations Management Group at the Indian Institute of Management Calcutta. Earlier (1990–97), he taught at Oklahoma State University and also at the Department of Mathematics, University of Louisiana at Lafayette (in 2001 and 2002). He was also an Honorary Visiting Scientist at the Indian Statistical Institute, Kolkata (during September 1997–August 1999). Professor Sarkar has over 50 research papers to his credit. His areas of interest are robust inference, minimum disparity inference, reliability, time series and forecasting, categorical data, and measurement error models. |NABENDU PAL (Ph.D., Statistics, University of Maryland, Baltimore County) is Professor of Statistics in the Department of Mathematics, University of Louisiana at Lafayette. Earlier (Spring 1989), he taught at University of Arkansas, Fayetteville. He was also a Visiting Scientist at Division of Theoretical Statistics and Mathematics, Indian Statistical Institute, Kolkata. A member of various national and international associations, Professor Pal has about 65 research papers to his credit. His areas of interest are decision theory and Bayesian analysis, reliability and life testing, and biostatistics.
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