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Short description Emphasizing the direct link between scientific research questions and data analysis, Modern Statistical and Computing Methods for the Behavioral and Educational Sciences Using R introduces current statistical methods, including the use of Monte Carlo simulation, bootstrapping, and randomization tests. Explicit instructions for using R are provided, and computer code and output are interwoven throughout to demonstrate how each analysis is carried out and how output is interpreted. The methods help students and researchers in the educational and behavioral sciences gain a better understanding of statistical concepts.
From the contents List of Figures.
List of Tables.
Foreword.
Preface.
Acknowledgments.
1. An Introduction to R.
1.1 Getting Started.
1.2 Arithmetic: R as a Calculator.
1.3 Computations in R: Functions.
1.4 Connecting Computations.
1.5 Data Structures: Vectors.
1.6 Getting Help.
1.7 Alternative Ways to Run R.
1.8 Extension: Matrices and Matrix Operations.
1.9 Further Reading.
Problems.
2. Data Representation and Preparation.
2.1 Tabular Data.
2.2 Data Entry.
2.3 Reading Delimited Data into R.
2.4 Data Structure: Data Frames.
2.5 Recording Syntax using Script Files.
2.6 Simple Graphing in R.
2.7 Extension: Logical Expressions and Graphs for Categorical Variables.
2.8 Further Reading.
Problems.
3. Data Exploration: One Variable.
3.1 Reading in the Data.
3.2 Non-Parametric Density Estimation.
3.3 Summarizing the Findings.
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.
