Comparing Groups : Randomization and Bootstrap Methods Using R


Andrew S. Zieffler
Bok Engelsk 2011 · Electronic books.
Annen tittel
Medvirkende
Utgitt
Hoboken : : Wiley, , 2011.
Omfang
1 online resource (332 p.)
Opplysninger
Description based upon print version of record.. - Comparing Groups: Randomization and Bootstrap Methods Using R; CONTENTS; List of Figures; List of Tables; Foreword; Preface; Acknowledgments; 1 An Introduction to R; 1.1 Getting Started; 1.1.1 Windows OS; 1.1.2 Mac OS; 1.1.3 Add-On Packages; 1.2 Arithmetic: R as a Calculator; 1.3 Computations in R: Functions; 1.4 Connecting Computations; 1.4.1 Naming Conventions; 1.5 Data Structures: Vectors; 1.5.1 Creating Vectors in R; 1.5.2 Computation with Vectors; 1.5.3 Character and Logical Vectors; 1.6 Getting Help; 1.7 Alternative Ways to Run R; 1.8 Extension: Matrices and Matrix Operations. - 1.8.1 Computation with Matrices1.9 Further Reading; Problems; 2 Data Representation and Preparation; 2.1 Tabular Data; 2.1.1 External Formats for Storing Tabular Data; 2.2 Data Entry; 2.2.1 Data Codebooks; 2.3 Reading Delimited Data into R; 2.3.1 Identifying the Location of a File; 2.3.2 Examining the Data in a Text Editor; 2.3.3 Reading Delimited Separated Data: An Example; 2.4 Data Structure: Data Frames; 2.4.1 Examining the Data Read into R; 2.5 Recording Syntax using Script Files; 2.5.1 Documentation File; 2.6 Simple Graphing in R. - 2.6.1 Saving Graphics to Insert into a Word-Processing File2.7 Extension: Logical Expressions and Graphs for Categorical Variables; 2.7.1 Logical Operators; 2.7.2 Measurement Level and Analysis; 2.7.3 Categorical Data; 2.7.4 Plotting Categorical Data; 2.8 Further Reading; Problems; 3 Data Exploration: One Variable; 3.1 Reading In the Data; 3.2 Nonparametric Density Estimation; 3.2.1 Graphically Summarizing the Distribution; 3.2.2 Histograms; 3.2.3 Kernel Density Estimators; 3.2.4 Controlling the Density Estimation; 3.2.5 Plotting the Estimated Density; 3.3 Summarizing the Findings. - 3.3.1 Creating a Plot for Publication3.3.2 Writing Up the Results for Publication; 3.4 Extension: Variability Bands for Kernel Densities; 3.5 Further Reading; Problems; 4 Exploration of Multivariate Data: Comparing Two Groups; 4.1 Graphically Summarizing the Marginal Distribution; 4.2 Graphically Summarizing Conditional Distributions; 4.2.1 Indexing: Accessing Individuals or Subsets; 4.2.2 Indexing Using a Logical Expression; 4.2.3 Density Plots of the Conditional Distributions; 4.2.4 Side-by-Side Box-and-Whiskers Plots; 4.3 Numerical Summaries of Data: Estimates of the Population Parameters. - 4.3.1 Measuring Central Tendency4.3.2 Measuring Variation; 4.3.3 Measuring Skewness; 4.3.4 Kurtosis; 4.4 Summarizing the Findings; 4.4.1 Creating a Plot for Publication; 4.4.2 Using Color; 4.4.3 Selecting a Color Palette; 4.5 Extension: Robust Estimation; 4.5.1 Robust Estimate of Location: The Trimmed Mean; 4.5.2 Robust Estimate of Variation: The Winsorized Variance; 4.6 Further Reading; Problems; 5 Exploration of Multivariate Data: Comparing Many Groups; 5.1 Graphing Many Conditional Distributions; 5.1.1 Panel Plots; 5.1.2 Side-by-Side Box-and-Whiskers Plots. - 5.2 Numerically Summarizing the Data. - A hands-on guide to using R to carry out key statistical practices in educational and behavioral sciences research Computing has become an essential part of the day-to-day practice of statistical work, broadening the types of questions that can now be addressed by research scientists applying newly derived data analytic techniques. Comparing Groups: Randomization and Bootstrap Methods Using R emphasizes the direct link between scientific research questions and data analysis. Rather than relying on mathematical calculations, this book focus on conceptual explanations and
Emner
Sjanger
Dewey
ISBN
9780470621691

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