This book provides the theoretical framework needed to build, analyze and interpret various statistical models. It helps readers choose the correct model, distinguish among various choices that best captures the data, or solve the problem at hand.
This is an introductory textbook on probability and statistics. The authors explain theoretical concepts in a step-by-step manner and provide practical examples. The introductory chapter in this book presents the basic concepts. Next, the authors discuss the measures of location, popular measures of spread, and measures of skewness and kurtosis. Probability theory, discrete distributions, and important continuous distributions that are often encountered in practical applications are analyzed. Mathematical Expectation is covered, along with Generating Functions and Functions of Random Variables. It discusses joint distributions, and novel methods to find the mean deviation of discrete and continuous statistical distributions.
* Provides insight on coding complex algorithms using the ‘loop unrolling technique’
* Covers illuminating discussions on Poisson limit theorem, central limit theorem, mean deviation generating functions, CDF generating function and extensive summary tables
* Contains extensive exercises at the end of each chapter and examples from interdisciplinary fields
Statistics for Scientists and Engineers is a great resource for students in engineering, physical sciences, and management, and also practicing engineers who require skill sets to model practical problems in a statistical setting.
Sobre o autor
Ramalingam Shanmugam is the Editor-in-Chief for the journals: Advances in Life Sciences and Health, International Journal of Research in Medical Sciences, and Global Journal of Research and Review. He is the Book-Review Editor of the Journal of Statistical Computation and Simulation. He directed Statistics Consulting Center in the Mississippi State University. He served the Argonne National Lab., University of Colorado, University of South Alabama and the Indian Statistical Institute. He has published 120 research articles and is a fellow of the International Statistical Institute. Currently, he is a professor in the School of Health Administration, Texas State University. He is a recipient of several research awards from the Texas State University.
Rajan Chattamvelli has worked as an Analyst Specialist at Denver Public Health and was a visiting professor at the Indian Institute of Management. He was Chair of the Department of Computer Applications at Presidency College and Periyar Maniammai University, India.
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