Produktbild: Gillespie, B: Guide to R for Social and Behavioral Science S
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Gillespie, B: Guide to R for Social and Behavioral Science S

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

11.03.2020

Verlag

Sage Publications

Seitenzahl

304

Maße (L/B/H)

23,1/18,3/1,5 cm

Gewicht

552 g

Sprache

Englisch

ISBN

978-1-5443-4402-7

Beschreibung

Rezension

This text is most timely given the popular use of R in many introductory stats courses throughout our universities. The reader will find the presentation of visuals, tips, and syntax in using R to be most impressive relative to what other books provide! This is a "must have" text for faculty and students embarking on a stats course that utilizes the R program.  Kyle Woosnam

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

11.03.2020

Verlag

Sage Publications

Seitenzahl

304

Maße (L/B/H)

23,1/18,3/1,5 cm

Gewicht

552 g

Sprache

Englisch

ISBN

978-1-5443-4402-7

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  • Produktbild: Gillespie, B: Guide to R for Social and Behavioral Science S
  • Preface
    Acknowledgments
    About the Authors
    Chapter 1 ¿ R and RStudio®
    Introduction
    Statistical Software Overview
    Downloading R and RStudio
    RStudio
    Finding R and RStudio Packages
    Opening Data
    Saving Data Files
    Conclusion
    Chapter 2 ¿ Data, Variables, and Data Management
    About the Data and Variables
    Structure and Organization of Classic "Wide" Datasets
    The General Social Survey
    Variables and Measurement
    Recoding Variables
    Logic of Coding
    Recoding Missing Values
    Computing Variables
    Removing Outliers
    Conclusion
    Chapter 3 ¿ Data Frequencies and Distributions
    Frequencies for Categorical Variables
    Cumulative Frequencies and Percentages
    Frequencies for Interval/Ratio Variables
    Histograms
    The Normal Distribution
    Non-Normal Distribution Characteristics
    Exporting Tables
    Conclusion
    Chapter 4 ¿ Central Tendency and Variability
    Measures of Central Tendency
    Measures of Variability
    The z-Score
    Selecting Cases for Analysis
    Conclusion
    Chapter 5 ¿ Creating and Interpreting Univariate and Bivariate Data Visualizations
    Introduction
    R's Color Palette
    Univariate Data Visualization
    Bivariate Data Visualization
    Exporting Figures
    Conclusion
    Chapter 6 ¿ Conceptual Overview of Hypothesis Testing and Effect Size
    Introduction
    Null and Alternative Hypotheses
    Statistical Significance
    Test Statistic Distributions
    Choosing a Test of Statistical Significance
    Hypothesis Testing Overview
    Effect Size
    Conclusion
    Chapter 7 ¿ Relationships Between Categorical Variables
    Single Proportion Hypothesis Test
    Goodness of Fit
    Bivariate Frequencies
    The Chi-Square Test of Independence (?2)
    Conclusion
    Chapter 8 ¿ Comparing One or Two Means
    Introduction
    One-Sample t-Test
    The Independent Samples t-Test
    Examples
    Additional Independent Samples t-Test Examples
    Effect Size for t-Test: Cohen's d
    Paired t-Test
    Conclusion
    Chapter 9 ¿ Comparing Means Across Three or More Groups (ANOVA)
    Analysis of Variance (ANOVA)
    ANOVA in R
    Two-Way Analysis of Variance
    Conclusion
    Chapter 10 ¿ Correlation and Bivariate Regression
    Review of Scatterplots
    Correlations
    Pearson's Correlation Coefficient
    Coefficient of Determination
    Correlation Tests for Ordinal Variables
    The Correlation Matrix
    Bivariate Linear Regression
    Logistic Regression
    Conclusion
    Chapter 11 ¿ Multiple Regression
    The Multiple Regression Equation
    Interaction Effects and Interpretation
    Logistic Regression
    Interpretation and Presentation of Logistic Regression Results
    Conclusion
    Chapter 12 ¿ Advanced Regression Topics
    Advanced Regression Topics
    Polynomials
    Logarithms
    Scaling Data
    Multicollinearity
    Multiple Imputation
    Further Exploration
    Conclusion
    Index