Chattamvelli (132 results)

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N.A. Condition: New. ISBN:9788184871685,304pp N.A.

N.A. Condition: New. ISBN:9788184875102,582pp N.A.

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Paperback. Condition: new. Paperback. Generating function (GF) is a mathematical technique to concisely represent a known ordered sequence into a simple continuous algebraic function in dummy variable(s). This Second Edition introduces commonly encountered generating functions (GFs) in engineering and applied sciences, such as ordinary GF (OGF), exponential GF (EGF), as also Dirichlet GF (DGF), Lambert GF (LGF), Logarithmic GF (LogGF), Hurwitz GF (HGF), Mittag-Lefler GF (MLGF), etc. This book is intended mainly for beginners in applied science and engineering fields to help them understand single-variable GFs and illustrate how to apply them in various practical problems. Specifically, the book discusses probability GFs (PGF), moment and cumulant GFs (MGF, CGF), mean deviation GFs (MDGF), survival function GFs (SFGF), rising and falling factorial GFs, factorial moment, and inverse factorial moment GFs. Applications of GFs in algebra, analysis of algorithms, bioinformatics, combinatorics, economics, finance, genomics, geometry, graph theory, management, number theory, polymer chemistry, reliability, statistics and structural engineering have been added to this new edition. This book is written in such a way that readers who do not have prior knowledge of the topic can easily follow through the chapters and apply the lessons learned in their respective disciplines. Specifically, the book discusses probability GFs (PGF), moment and cumulant GFs (MGF, CGF), mean deviation GFs (MDGF), survival function GFs (SFGF), rising and falling factorial GFs, factorial moment, and inverse factorial moment GFs. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condition: new. Paperback. This book introduces descriptive statistics and covers a broad range of topics of interest to students and researchers in various applied science disciplines. This includes measures of location, spread, skewness, and kurtosis; absolute and relative measures; and classification of spread, skewness, and kurtosis measures, L-moment based measures, van Zwet ordering of kurtosis, and multivariate kurtosis. Several novel topics are discussed including the recursive algorithm for sample variance; simplification of complicated summation expressions; updating formulas for sample geometric, harmonic and weighted means; divide-and-conquer algorithms for sample variance and covariance; L-skewness; spectral kurtosis, etc. A large number of exercises are included in each chapter that are drawn from various engineering fields along with examples that are illustrated using the R programming language. Basic concepts are introduced before moving on to computational aspects. Some applicationsin bioinformatics, finance, metallurgy, pharmacokinetics (PK), solid mechanics, and signal processing are briefly discussed. Every analyst who works with numeric data will find the discussion very illuminating and easy to follow. This book introduces descriptive statistics and covers a broad range of topics of interest to students and researchers in various applied science disciplines. and classification of spread, skewness, and kurtosis measures, L-moment based measures, van Zwet ordering of kurtosis, and multivariate kurtosis. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Condition: New. Second Edition 2023 NO-PA16APR2015-KAP.

Condition: New.

Hardcover. Condition: new. Hardcover. This book introduces descriptive statistics and covers a broad range of topics of interest to students and researchers in various applied science disciplines. This includes measures of location, spread, skewness, and kurtosis; absolute and relative measures; and classification of spread, skewness, and kurtosis measures, L-moment based measures, van Zwet ordering of kurtosis, and multivariate kurtosis. Several novel topics are discussed including the recursive algorithm for sample variance; simplification of complicated summation expressions; updating formulas for sample geometric, harmonic and weighted means; divide-and-conquer algorithms for sample variance and covariance; L-skewness; spectral kurtosis, etc. A large number of exercises are included in each chapter that are drawn from various engineering fields along with examples that are illustrated using the R programming language. Basic concepts are introduced before moving on to computational aspects. Some applicationsin bioinformatics, finance, metallurgy, pharmacokinetics (PK), solid mechanics, and signal processing are briefly discussed. Every analyst who works with numeric data will find the discussion very illuminating and easy to follow. This book introduces descriptive statistics and covers a broad range of topics of interest to students and researchers in various applied science disciplines. and classification of spread, skewness, and kurtosis measures, L-moment based measures, van Zwet ordering of kurtosis, and multivariate kurtosis. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Condition: New. 2nd ed. 2023 edition NO-PA16APR2015-KAP.

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Condition: New. In English.

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Paperback. Condition: Brand New. 2nd edition. 130 pages. 9.44x6.61x9.45 inches. In Stock.

Hardcover. Condition: Brand New. 2nd edition. 141 pages. 9.45x6.61x0.51 inches. In Stock.

Hardback. Condition: New. New copies no faults.275 pages. large format HB.

Hardcover. Condition: new. Hardcover. This book focuses on correlation coefficients and its applications in applied science fields. The book begins by describing the historical development and various types of correlations. Rank correlation methods including Pearsons, Spearmans, and Kendalls correlation are discussed at length. The book also discusses sampling distribution of correlation coefficients and applications of correlations in various fields. The book presents novel topics such as (i) a quick analytical method to approximate Pearson's correlation, (ii) single-variable correlation, (iii) fractional co-skewness and co-kurtosis, and (iv) the fallacy on correlation between the sample mean and sample variance. This book is ideal for courses on mathematical statistics, engineering statistics, and exploratory data analysis and is primarily aimed at upper-undergraduate and graduate level students. The book is also useful for researchers and professionals in various fields who are interested in data analysis. The book presents novel topics such as (i) a quick analytical method to approximate Pearson's correlation, (ii) single-variable correlation, (iii) fractional co-skewness and co-kurtosis, and (iv) the fallacy on correlation between the sample mean and sample variance. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Condition: New. In English.

Condition: New.

Condition: New. 2nd ed. 2023 edition NO-PA16APR2015-KAP.

Condition: As New. Unread book in perfect condition.

Condition: New. In English.

Condition: New.

Condition: New. 2nd ed. 2023 edition NO-PA16APR2015-KAP.