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001475985 001__ 1475985
001475985 003__ OCoLC
001475985 005__ 20231003174627.0
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001475985 019__ $$a1394120485
001475985 020__ $$a9783031330735$$q(electronic bk.)
001475985 020__ $$a3031330730$$q(electronic bk.)
001475985 020__ $$z3031330722
001475985 020__ $$z9783031330728
001475985 0247_ $$a10.1007/978-3-031-33073-5$$2doi
001475985 035__ $$aSP(OCoLC)1394000917
001475985 040__ $$aYDX$$beng$$cYDX$$dGW5XE$$dEBLCP$$dOCLCQ$$dOCLCO
001475985 049__ $$aISEA
001475985 050_4 $$aQH323.5
001475985 08204 $$a570.1/5195$$223/eng/20230828
001475985 1001_ $$aMoscarelli, Marco.
001475985 24510 $$aBiostatistics with 'R' :$$ba guide for medical doctors /$$cMarco Moscarelli.
001475985 260__ $$aCham :$$bSpringer,$$c2023.
001475985 300__ $$a1 online resource
001475985 504__ $$aIncludes bibliographical references.
001475985 5050_ $$aIntro -- Foreword -- Preface -- Contents -- Chapter 1: Introduction -- 1.1 Introduction -- 1.2 What Is the Dataset About? -- 1.3 What You Will Learn -- 1.4 Why This Book? -- 1.5 How This Book Works -- 1.6 What Is "R" (and R-Studio)? -- 1.7 Who Is This Book For? -- Chapter 2: How "R" Works -- 2.1 Downloading "R" and R-Studio -- 2.2 What R-Studio Looks Like -- 2.3 Running Simple Codes in the "R"-Console -- 2.4 To Practice with a More Advanced Code -- 2.5 Getting Help in "R" -- 2.6 The Hash Symbol # -- 2.7 The Problem of Missing Data -- 2.8 Misspelling the Code
001475985 5058_ $$a2.9 Setting the Working Directory -- 2.10 Working with Scripts -- 2.11 R-Packages -- 2.12 Installing R-Packages -- 2.13 Loading R-Packages -- 2.14 How Many R-Packages Do We Need? -- 2.15 Conclusions -- Further Readings -- Chapter 3: Exploratory Data Analysis in "R" -- 3.1 Software and R-Package Required for This Chapter -- 3.2 Importing a Dataset into "R" -- 3.3 Fundamental Function to Explore a Dataset -- 3.4 Subsetting -- 3.5 Subsetting with Base-R -- 3.6 More Examples of Basic Subsetting -- 3.7 The Attach Function -- 3.8 Storing a Dataset as a Tibble for Use with the tidyverse R-Package
001475985 5058_ $$a3.9 Frequently Used Subsetting Functions -- 3.10 Conclusions -- Further Readings -- Chapter 4: Data Types in "R" -- 4.1 Software and R-Packages Required for This Chapter -- 4.2 Where to Find the Example Dataset and the Script for This Chapter -- 4.3 What Is the Nature of Our Data? -- 4.4 Numeric Data -- 4.5 Integer -- 4.6 Character -- 4.7 Factors -- 4.8 Variable Classification -- 4.9 Misleading Data Encoding -- 4.10 Different Types of Variables Need Different Types of Statistical Analysis -- 4.11 Data Transformation and the Benefit of Continuous Variables -- 4.12 Missing Values
001475985 5058_ $$a4.13 The CreateTableOne Function -- 4.14 Conclusion -- Further Readings -- Chapter 5: Data Distribution -- 5.1 Software and R-Packages Required for This Chapter -- 5.2 Where to Download the Example Dataset and the Script for This Chapter -- 5.3 Normality Testing -- 5.4 Histogram -- 5.5 Normality Testing -- 5.6 More About Visual Inspection with Regard to Normality -- 5.7 Do We Need to Test for Normality in All Cases? -- 5.8 Central Limit Theory -- 5.9 Properties of Normal Distribution -- 5.10 Subsetting for Normality Testing -- 5.11 Hint from the Grammar of Graphic -- 5.12 Boxplot
001475985 5058_ $$a5.13 How to Treat Non-numeric Variables -- 5.14 Plotting Categorical Variables -- 5.15 Conclusion -- Further Readings -- Chapter 6: Precision, Accuracy and Indices of Central Tendency -- 6.1 Software and R-Packages Required for This Chapter -- 6.2 Where to Download the Example Dataset and the Script for This Chapter -- 6.3 Precision -- 6.4 The Relation Between Sample Size and Precision -- 6.5 Variance and Standard Deviation -- 6.6 Population and Sample Variance -- 6.7 Standard Error of the Mean vs Standard Deviation -- 6.8 Accuracy and Confidence Intervals -- 6.9 Mean, Median, Mode
001475985 506__ $$aAccess limited to authorized users.
001475985 520__ $$aThis book aims not only to introduce fundamental biostatistics topics but to explain them through R-project (R-studio). 'R' is perhaps the more used statistical software in the medical field. It is structured as a 'scientific journey' and comes with a sham yet realistic dataset ready to be analysed. The dataset along with the R-script can be downloaded from GitHub, and each chapter has dedicated scripts that will enhance the understanding of R and biostatistics. Specifically designed for whoever works in the medical-academic environment, this practical guide will help the reader to become familiar with basic to advanced biostatistics topic (descriptive - analysis / regression etc.) and to gain solid knowledge of R. .
001475985 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed August 28, 2023).
001475985 650_0 $$aBiometry$$xData processing.
001475985 650_0 $$aR (Computer program language)
001475985 650_6 $$aBiométrie$$xInformatique.
001475985 650_6 $$aR (Langage de programmation)
001475985 655_0 $$aElectronic books.
001475985 77608 $$iPrint version: $$z3031330722$$z9783031330728$$w(OCoLC)1375991571
001475985 852__ $$bebk
001475985 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-33073-5$$zOnline Access$$91397441.1
001475985 909CO $$ooai:library.usi.edu:1475985$$pGLOBAL_SET
001475985 980__ $$aBIB
001475985 980__ $$aEBOOK
001475985 982__ $$aEbook
001475985 983__ $$aOnline
001475985 994__ $$a92$$bISE