Correlation in Engineering and the Applied Sciences: Applications in R: Synthesis Lectures on Mathematics & Statistics
Autor Rajan Chattamvellien Limba Engleză Hardback – 9 mar 2024
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Specificații
ISBN-13: 9783031510144
ISBN-10: 3031510143
Pagini: 179
Ilustrații: XVI, 179 p. 10 illus., 8 illus. in color.
Dimensiuni: 168 x 240 mm
Greutate: 0.48 kg
Ediția:2024
Editura: Springer Nature Switzerland
Colecția Springer
Seria Synthesis Lectures on Mathematics & Statistics
Locul publicării:Cham, Switzerland
ISBN-10: 3031510143
Pagini: 179
Ilustrații: XVI, 179 p. 10 illus., 8 illus. in color.
Dimensiuni: 168 x 240 mm
Greutate: 0.48 kg
Ediția:2024
Editura: Springer Nature Switzerland
Colecția Springer
Seria Synthesis Lectures on Mathematics & Statistics
Locul publicării:Cham, Switzerland
Cuprins
Measures of Association.- Pearson’s Correlation.- Rank Correlation.- Distribution of Correlation.- Applications of Correlation.
Notă biografică
Rajan Chattamvelli, Ph.D., is a Professor in the School of Computer Science and Engineering at Amrita University, India. He has published more than 20 research articles in international journals, and his research interests include computational statistics, design of algorithms, parallel computing, data mining, machine learning, blockchain, combinatorics, and big data analytics.
Textul de pe ultima copertă
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 Pearson’s, Spearman’s, and Kendall’s 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.
In addition, this book:
In addition, this book:
- Combines theory with numerical examples and includes the latest developments in the field
- Presents computer code in R software and features plentiful exercises throughout
- Features discussions on measures of association, rank correlation, and the distribution
Caracteristici
Combines theory with numerical examples and includes the latest developments in the field Presents computer code in R software and features plentiful exercises throughout Features discussions on measures of association, rank correlation, and the distribution