JOY OF STATS 2/E

Roberta Garner is Professor of Sociology at DePaul University in Chicago. She is the author of The Joy of Stats: A Short Guide to Introductory Statistics in the Social Sciences, Second Edition (2010). She teaches courses on theory, research design, statistics, and Greek mythology.

"This is a great book for social science students. Clearly written, with many examples, Garner certainly makes learning and teaching introductory statistics a joy!" - Nikolaos Liodakis, Wilfrid Laurier University

This is a great book for social science students... It introduces them to a whole new way of looking at numbers along with real-world applications. Clearly written, with many examples, Garner's The Joy of Stats certainly makes learning and teaching introductory statistics a joy! -- Nikolaos Liodakis, Wilfrid Laurier University The Joy of Stats is indeed a joy to use in the classroom. The book is approachable, thorough without being overwhelming and with the right balance of specific examples and general principles. I've used it many times for a third year methods course and will continue to do so, particularly with the additional material in this new edition. -- Philippe Couton, University of Ottawa

List of Figures and Tables Acknowledgments Preface Chapter One: Basic Concepts Part I: Variables Level of Measurement Dichotomous Variables Operationalized Variables Independent (IV) and Dependent (DV) Variables Causality Units of Analysis: Individual and Place-level Data Part II: Thinking about Procedures Descriptive and Inferential Statistics Difference Observing and Estimating Conclusion Key terms Chapter Two: Describing Distributions Part I: Frequency Distributions Part II: Summary Measures Measures of Central Tendency (Mean, Median, Mode) Measures of Dispersion (or Variability) Categoric Variables: Index of Diversity and Index of Qualitative Variation Part III: Graphing and Visual Displays of Distributions Part IV: Standardized Scores or Z-scores The Mathematical Imagination: The Magic of Z-scores Math Interlude: Chebycheff's Inequality Conclusion Key Terms Chapter Three: Statistical Inference Part I: Thinking about Statistical Inference Statistical Inference: What Are We Trying To Do? Variability The Mathematical Imagination: A World Without Variability The Normal Curve The Mathematical Imagination: Mild and Wild Randomness Sampling Distributions and the Normal Curve Sampling Error: Variability of the Sampling Distribution The Central Limit Theorem Math Thoughts Underlying Distributions and Sampling Distributions The Sampling Distribution of a Proportion Part II: Doing Statistical Inference The Logic of Statistical Inference Confidence Intervals Hypothesis Testing (The Null Hypothesis and T-tests) Conclusion Key Terms Chapter Four: Relationships Among Variables Part I: An Overview - Thinking About Variable Relationships Four Types of Data Analysis Techniques Beyond Bivariate Analysis: Adding Variables and Staying Alert Part II: Data Analysis Techniques Section One: Regression Analysis Math Interlude: The Natural Log Transformation Section Two: Crosstabs Section Three: ANOVA Section Four: Logistic Regression Conclusion Key Terms Conclusion How To? Choosing a Data Analysis Technique Regression Analysis Pearson's Correlation Coefficient The Bivariate Regression Equation Coefficient of Determination (aka "R-squared") Crosstabs and Related Procedures Computing Chi-Square Joint and Marginal Distributions More about Running Percentages Measures of Association ANOVA and the F-test T-tests One-Sample T-test Independent Samples T-test Exercises Questions Answers Math Refresher Tips for Studying Math Estimating From Common Sense to Formula The Number Line Greater and Lesser Absolute Value Fractions and Other Proportions Decimal Fractions Percent Comparing Fractions Computing Percent Change and Percentage Point Change Operations Addition Multiplication Subtraction Division Word or Story Problems Squaring, Higher Powers, and Square Roots Squaring Higher Powers Square Roots Scientific Notation Manipulating Formulas The Coordinate Plane, Ordered Pairs, and Functions Appendix Tables of Probability Distributions Table 26: Critical Values for the Z-distribution Table 27: Critical Values for the T-distribution Table 28: Critical Values for the Chi-Square Distribution Table 29: Critical Values for the F-distribution Bibliography, Reading Suggestions, and Works Cited Index