Springer, 2024. — 192 p. — (Synthesis Lectures on Mathematics & Statistics). — ISBN 3031510143.
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.
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