Name: Descriptive Statistics for Scientists and Engineers: Applications in R (en Inglés)
SKU: 55197571
Price: 866.58 MXN
Availability: InStock
Author: Chattamvelli, Rajan ; Shanmugam, Ramalingam
ISBN: 9783031323294

portada Descriptive Statistics for Scientists and Engineers: Applications in R (en Inglés)

Descriptive Statistics for Scientists and Engineers: Applications in R (en Inglés)

Formato

Libro Físico

Autor

Ramalingam Shanmugam

Rajan Chattamvelli

Editorial

Springer

Idioma

Inglés

N° páginas

130

Encuadernación

Tapa Dura

Dimensiones

24.4x17.4x1.4 cm

Peso

0.41 kg.

ISBN13

9783031323294

N° edición

0002

Categorías

Probabilidad y estadística
Matemáticas aplicadas
Ingeniería: general

Descriptive Statistics for Scientists and Engineers: Applications in R (en Inglés)

Ramalingam Shanmugam (Autor) · Rajan Chattamvelli (Autor) · Springer · Tapa Dura

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Reseña del libro "Descriptive Statistics for Scientists and Engineers: Applications in R (en Inglés)"

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.