R
Reference documents in R.
Documents in R
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This book provides an integrated treatment of statistical inference techniques in data science using the R Statistical Software. It provides a much-needed, easy-to-follow introduction to statistics and the R programming language.
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The aim of the book is to introduce you to key parts of the modern statistical toolkit. It teaches you: - Data wrangling - importing, formatting, reshaping, merging, and filtering data in R.
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This book takes readers on a journey of statistical discovery using the freeware R. This book is written in an irreverent style and follows the same ground breaking structure and pedagogical approach. The core material is enhanced by a cast of characters to help the reader on their way, hundreds of examples, self assessment tests to consolidate knowledge, and additional website material for those wanting to learn more.
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This book is for those interested in becoming crime analysts, focusing on learning statistics without delving too deeply into mathematics. Emphasizes practical applications by utilizing R for data analysis, ensuring students can develop relevant skills beyond the university.
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This book serves as an excellent tutorial on the R language, providing examples that illustrate programming concepts in the context of practical statistical modelling and computational problems. Understanding of quantitative methods and apply to real world applications.
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This book systematically covers Empirical Likelihood methods in most important topics in Survival Analysis: the Kaplan–Meier and the Nelson–Aalen estimator, the log rank test, the Cox proportional hazards model and the accelerated failure time models.
