Central Library

Normal view MARC view ISBD view

Descriptive Statistics for Scientists and Engineers [electronic resource] : Applications in R / by Rajan Chattamvelli, Ramalingam Shanmugam.

By: Chattamvelli, Rajan [author.].
Contributor(s): Shanmugam, Ramalingam [author.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Synthesis Lectures on Mathematics & Statistics: Publisher: Cham : Springer Nature Switzerland : Imprint: Springer, 2023Edition: 2nd ed. 2023.Description: XI, 130 p. 8 illus., 3 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783031323300.Subject(s): Engineering mathematics | Engineering -- Data processing | Quantitative research | Statistics  | Probabilities | Mathematical and Computational Engineering Applications | Data Analysis and Big Data | Applied Statistics | Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences | Statistics | Probability TheoryAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 620 Online resources: Click here to access online
Contents:
Descriptive Statistics -- Measures of Location -- Measures of Spread -- Measures of Skewness and Kurtosis.
In: Springer Nature eBookSummary: 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 applications in 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. In addition, this book: Provides exercises throughout that are illustrated via the R programming language Assists readers to do various numeric data transformations, normality testing, etc. Aids readers to build, analyze, and interpret various descriptive statistical models Presents numerous examples from various engineering fields.
    average rating: 0.0 (0 votes)
No physical items for this record

Descriptive Statistics -- Measures of Location -- Measures of Spread -- Measures of Skewness and Kurtosis.

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 applications in 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. In addition, this book: Provides exercises throughout that are illustrated via the R programming language Assists readers to do various numeric data transformations, normality testing, etc. Aids readers to build, analyze, and interpret various descriptive statistical models Presents numerous examples from various engineering fields.

There are no comments for this item.

Log in to your account to post a comment.