图书简介

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

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