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020 _a9783031024306
_9978-3-031-02430-6
024 7 _a10.1007/978-3-031-02430-6
_2doi
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072 7 _aPB
_2bicssc
072 7 _aMAT000000
_2bisacsh
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082 0 4 _a510
_223
100 1 _aChattamvelli, Rajan.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_978791
245 1 0 _aContinuous Distributions in Engineering and the Applied Sciences -- Part I
_h[electronic resource] /
_cby Rajan Chattamvelli, Ramalingam Shanmugam.
250 _a1st ed. 2021.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2021.
300 _aXXII, 151 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSynthesis Lectures on Mathematics & Statistics,
_x1938-1751
505 0 _aList of Figures -- List of Tables -- Preface -- Glossary of Terms -- Continuous Random Variables -- Rectangular Distribution -- Exponential Distribution -- Beta Distribution -- Arcsine Distribution -- Gamma Distribution -- Cosine Distribution -- Normal Distribution -- Cauchy Distribution -- Bibliography -- Authors' Biographies -- Index.
520 _aThis is an introductory book on continuous statistical distributions and its applications. It is primarily written for graduate students in engineering, undergraduate students in statistics, econometrics, and researchers in various fields. The purpose is to give a self-contained introduction to most commonly used classical continuous distributions in two parts. Important applications of each distribution in various applied fields are explored at the end of each chapter. A brief overview of the chapters is as follows. Chapter 1 discusses important concepts on continuous distributions like location-and-scale distributions, truncated, size-biased, and transmuted distributions. A theorem on finding the mean deviation of continuous distributions, and its applications are also discussed. Chapter 2 is on continuous uniform distribution, which is used in generating random numbers from other distributions. Exponential distribution is discussed in Chapter 3, and its applications briefly mentioned. Chapter 4 discusses both Beta-I and Beta-II distributions and their generalizations, as well as applications in geotechnical engineering, PERT, control charts, etc. The arcsine distribution and its variants are discussed in Chapter 5, along with arcsine transforms and Brownian motion. This is followed by gamma distribution and its applications in civil engineering, metallurgy, and reliability. Chapter 7 is on cosine distribution and its applications in signal processing, antenna design, and robotics path planning. Chapter 8 discusses the normal distribution and its variants like lognormal, and skew-normal distributions. The last chapter of Part I is on Cauchy distribution, its variants and applications in thermodynamics, interferometer design, and carbon-nanotube strain sensing. A new volume (Part II) covers inverse Gaussian, Laplace, Pareto, 2, T, F, Weibull, Rayleigh, Maxwell, and Gumbel distributions.
650 0 _aMathematics.
_911584
650 0 _aStatistics .
_931616
650 0 _aEngineering mathematics.
_93254
650 1 4 _aMathematics.
_911584
650 2 4 _aStatistics.
_914134
650 2 4 _aEngineering Mathematics.
_93254
700 1 _aShanmugam, Ramalingam.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_978792
710 2 _aSpringerLink (Online service)
_978793
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031002762
776 0 8 _iPrinted edition:
_z9783031013027
776 0 8 _iPrinted edition:
_z9783031035586
830 0 _aSynthesis Lectures on Mathematics & Statistics,
_x1938-1751
_978794
856 4 0 _uhttps://doi.org/10.1007/978-3-031-02430-6
912 _aZDB-2-SXSC
942 _cEBK
999 _c84658
_d84658