Gillespie, Brian Joseph <br/><br/>
A guide to R for social and behavioral science statistics 

 - Los Angeles  Sage Publications, Inc.  2021 
 - xv284 p. 
<br/><br/>Chapter 1 • R and RStudio® <br/>Introduction<br/> <br/>Statistical Software Overview<br/> <br/>Downloading R and RStudio<br/> <br/>RStudio<br/> <br/>Finding R and RStudio Packages<br/> <br/>Opening Data<br/> <br/>Saving Data Files<br/> <br/>Conclusion<br/> <br/>  Chapter 2 • Data, Variables, and Data Management <br/>About the Data and Variables<br/> <br/>Structure and Organization of Classic “Wide” Datasets<br/> <br/>The General Social Survey<br/> <br/>Variables and Measurement<br/> <br/>Recoding Variables<br/> <br/>Logic of Coding<br/> <br/>Recoding Missing Values<br/> <br/>Computing Variables<br/> <br/>Removing Outliers<br/> <br/>Conclusion<br/> <br/>  Chapter 3 • Data Frequencies and Distributions <br/>Frequencies for Categorical Variables<br/> <br/>Cumulative Frequencies and Percentages<br/> <br/>Frequencies for Interval/Ratio Variables<br/> <br/>Histograms<br/> <br/>The Normal Distribution<br/> <br/>Non-Normal Distribution Characteristics<br/> <br/>Exporting Tables<br/> <br/>Conclusion<br/> <br/>  Chapter 4 • Central Tendency and Variability <br/>Measures of Central Tendency<br/> <br/>Measures of Variability<br/> <br/>The z-Score<br/> <br/>Selecting Cases for Analysis<br/> <br/>Conclusion<br/> <br/>  Chapter 5 • Creating and Interpreting Univariate and Bivariate Data Visualizations <br/>Introduction<br/> <br/>R’s Color Palette<br/> <br/>Univariate Data Visualization<br/> <br/>Bivariate Data Visualization<br/> <br/>Exporting Figures<br/> <br/>Conclusion<br/> <br/>  Chapter 6 • Conceptual Overview of Hypothesis Testing and Effect Size <br/>Introduction<br/> <br/>Null and Alternative Hypotheses<br/> <br/>Statistical Significance<br/> <br/>Test Statistic Distributions<br/> <br/>Choosing a Test of Statistical Significance<br/> <br/>Hypothesis Testing Overview<br/> <br/>Effect Size<br/> <br/>Conclusion<br/> <br/>  Chapter 7 • Relationships Between Categorical Variables <br/>Single Proportion Hypothesis Test<br/> <br/>Goodness of Fit<br/> <br/>Bivariate Frequencies<br/> <br/>The Chi-Square Test of Independence (?2)<br/> <br/>Conclusion<br/> <br/>  Chapter 8 • Comparing One or Two Means <br/>Introduction<br/> <br/>One-Sample t-Test<br/> <br/>The Independent Samples t-Test<br/> <br/>Examples<br/> <br/>Additional Independent Samples t-Test Examples<br/> <br/>Effect Size for t-Test: Cohen’s d<br/> <br/>Paired t-Test<br/> <br/>Conclusion<br/> <br/>  Chapter 9 • Comparing Means Across Three or More Groups (ANOVA) <br/>Analysis of Variance (ANOVA)<br/> <br/>ANOVA in R<br/> <br/>Two-Way Analysis of Variance<br/> <br/>Conclusion<br/> <br/>  Chapter 10 • Correlation and Bivariate Regression <br/>Review of Scatterplots<br/> <br/>Correlations<br/> <br/>Pearson’s Correlation Coefficient<br/> <br/>Coefficient of Determination<br/> <br/>Correlation Tests for Ordinal Variables<br/> <br/>The Correlation Matrix<br/> <br/>Bivariate Linear Regression<br/> <br/>Logistic Regression<br/> <br/>Conclusion<br/> <br/>  Chapter 11 • Multiple Regression <br/>The Multiple Regression Equation<br/> <br/>Interaction Effects and Interpretation<br/> <br/>Logistic Regression<br/> <br/>Interpretation and Presentation of Logistic Regression Results<br/> <br/>Conclusion<br/> <br/>  Chapter 12 • Advanced Regression Topics <br/>Advanced Regression Topics<br/> <br/>Polynomials<br/> <br/>Logarithms<br/> <br/>Scaling Data<br/> <br/>Multicollinearity<br/> <br/>Multiple Imputation<br/> <br/>Further Exploration<br/> <br/>Conclusion<br/> <br/> <br/>Index 
<br/><br/> A Guide to R for Social and Behavioral Science Statistics is a short, accessible book for learning R. This handy guide contains basic information on statistics for undergraduates and graduate students, shown in the R statistical language using RStudio®. The book is geared toward social and behavioral science statistics students, especially those with no background in computer science. Written as a companion book to be used alongside a larger introductory statistics text, the text follows the most common progression of statistics for social scientists. The guide also serves as a companion for conducting data analysis in a research methods course or as a stand-alone R and statistics text. This guide can teach anyone how to use R to analyze data, and uses frequent reminders of basic statistical concepts to accompany instructions in R to help walk students through the basics of learning how to use R for statistics. <br/><br/><br/> 
<br/><br/><label>ISBN: </label>9781544344027 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Psychology--Statistical methods<br/>R (Computer program language)<br/>Social sciences--Statistical methods
<br/><br/><label>Dewey Class. No.: </label>519.502855133  / GIL