03450nam a22005535i 4500001001800000003000900018005001700027007001500044008004100059020003700100024003500137050001400172072001600186072002300202072001500225100008900240245012600329250001800455264006900473300006400542336002600606337002600632338003600658347002400694490006300718505013800781520128400919650002502203650002302228650003402251650002702285650002702312650003602339650003102375650004302406650003402449650003602483650003202519650003602551710003402587773002602621776003602647776003602683776003602719830006302755856004602818912001502864999001702879978-3-031-51015-1DE-He21320251030111505.0cr nn 008mamaa240308s2024    sz |    s    |||| 0|eng d  a97830315101519978-3-031-51015-17 a10.1007/978-3-031-51015-12doi 4aQA276-280 7aPBT2bicssc 7aMAT0290002bisacsh 7aPBT2thema1 aChattamvelli, Rajan.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut97260910aCorrelation in Engineering and the Applied Sciencesh[electronic resource] :bApplications in R /cby Rajan Chattamvelli.  a1st ed. 2024. 1aCham :bSpringer Nature Switzerland :bImprint: Springer,c2024.  aXVI, 179 p. 10 illus., 8 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda1 aSynthesis Lectures on Mathematics & Statistics,x1938-17510 aMeasures of Association -- Pearson’s Correlation -- Rank Correlation -- Distribution of Correlation -- Applications of Correlation.  aThis 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: 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. 0aStatistics .965982 0aStatistics.965982 0aMultivariate analysis.972610 0aMeasure theory.971216 0aQuantitative research. 0aMathematical statistics.96723314aApplied Statistics.96598624aStatistical Theory and Methods.97261124aMultivariate Analysis.97261224aMeasure and Integration.97121924aData Analysis and Big Data.24aMathematical Statistics.9672332 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978303151014408iPrinted edition:z978303151016808iPrinted edition:z9783031510175 0aSynthesis Lectures on Mathematics & Statistics,x1938-175140uhttps://doi.org/10.1007/978-3-031-51015-1  aZDB-2-SXSC  c58174d58174