Statistics for Scientists and Engineers

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A01=Rajan Chattamvelli
A01=Ramalingam Shanmugam
Analysis of variance
ANOVA
area based methods
arithmetic mean
Author_Rajan Chattamvelli
Author_Ramalingam Shanmugam
Bayes theorem
binomial theorem
Category=PBT
Category=PDE
Category=TBJ
characteristic functions
CLT
conditional probability
Confidence intervals
correlation measures
cumulant generating function
data discretization
data transformations
discrete distributions
eq_bestseller
eq_isMigrated=1
eq_nobargain
eq_non-fiction
eq_science
eq_tech-engineering
Estimation
Expectation
Functions of Random Variables
generating functions
geometric and harmonic means
Jacobian method
Joint distributions
kurtosis
Law of Large Numbers
mean
mean deviation (MD)
measures of location
measures of skewness
median and mode
moment generating function
moments
multivariate kurtosis
Order Statistics
popular measures of spread
probabilistic methods
probability generating function
probability theory
r-charts
recurrence relations
Regression
reliability analysis
Snedecor's F
spectral kurtosis
Statistical Quality Control
Student's T
tail probabilities
Tests of Hypotheses
variance
weighted mean
xbar

Product details

  • ISBN 9781118228968
  • Weight: 794g
  • Dimensions: 160 x 241mm
  • Publication Date: 11 Sep 2015
  • Publisher: John Wiley & Sons Inc
  • Publication City/Country: US
  • Product Form: Hardback
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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.

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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