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An R companion for applied statistics II: multivariable and multivariate techniques

By: Rasco, DanneyMaterial type: TextTextPublication details: California Sage Publications, Inc. 2021 Description: xv, 267 pISBN: 9781071815571Subject(s): R (Computer program language) | Commercial statistics | Statistics--Computer programs | Statistics--Data processingDDC classification: 519.502855133 Summary: An R Companion for Applied Statistics II: Multivariable and Multivariate Techniques breaks the language of the R software down into manageable chunks in order to help students learn how to use R to analyze multivariate data. The book focuses on the statistics generally covered in an intermediate or multivariate statistics course and provides one or two ways to run each analysis in R. The book has been designed to be an R companion to Rebecca M. Warner's Applied Statistics II: Third Edition, and includes end-of-chapter instructions for replicating the examples from that book in R. However, this text can also be used as a stand-alone R guide for a multivariate statistics course, without reference to the Warner text. Datasets and scripts to run the examples are provided on an accompanying website.
List(s) this item appears in: Operation & quantitative Techniques | Non Fiction
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Item type Current library Collection Call number Copy number Status Date due Barcode
Book Book Indian Institute of Management LRC
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Operations Management & Quantitative Techniques 519.502855133 RAS (Browse shelf(Opens below)) 1 Available 004357

An R Companion for Applied Statistics II: Multivariable and Multivariate Techniques breaks the language of the R software down into manageable chunks in order to help students learn how to use R to analyze multivariate data. The book focuses on the statistics generally covered in an intermediate or multivariate statistics course and provides one or two ways to run each analysis in R. The book has been designed to be an R companion to Rebecca M. Warner's Applied Statistics II: Third Edition, and includes end-of-chapter instructions for replicating the examples from that book in R. However, this text can also be used as a stand-alone R guide for a multivariate statistics course, without reference to the Warner text. Datasets and scripts to run the examples are provided on an accompanying website.



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