Title Page -- Copyright -- Preface -- Acknowledgments -- PART I: INTRODUCTION AND DESCRIPTIVE STATISTICS -- 1. Introduction and Overview -- 1.1 Chapter Overview -- 1.2 Statistics and Social Work -- 1.3 Science and Research -- 1.4 Variables and Measurement -- 1.5 Samples and Populations -- 1.6 Descriptive and Inferential Statistics -- 1.7 Univariate, Bivariate, and Multivariate Statistics -- 1.8 Random Assignment -- 1.9 Levels of Measurement -- 1.9.1 Basics -- 1.9.2 Fine Points -- 1.10 Chapter Summary -- 1.11 Problems and Questions -- 2. Data Presentation -- 2.1 Chapter Overview -- 2.2 Frequency Distributions and Tables -- 2.3 Figures -- 2.4 Chapter Summary -- 2.5 Problems and Questions -- 3. Central Tendency -- 3.1 Chapter Overview -- 3.2 Key Concepts in Univariate Descriptive Statistics -- 3.3 Three Key Measures of Central Tendency -- 3.4 The Mode -- 3.5 The Median -- 3.6 The Mean -- 3.7 Choosing Between Measures -- 3.8 Chapter Summary -- 3.9 Problems and Questions -- 4. Measures of Variability -- 4.1 Chapter Overview -- 4.2 The Concept of Variability -- 4.3 Assessing the Variability of Categorical Variables -- 4.4 The Range -- 4.5 The Interquartile Range -- 4.6 The Mean Deviation -- 4.7 The Standard Deviation -- 4.8 The Variance -- 4.9 Chapter Summary -- 4.10 Problems and Questions -- 5. Shape of Distribution -- 5.1 Chapter Overview -- 5.2 The Normal Distribution -- 5.3 Skewed Distributions -- 5.3.1 Characteristics -- 5.3.2 Skewness and Measures of Central Tendency -- 5.4 Kurtosis -- 5.5 Uniform and Bimodal Distributions -- 5.6 Percentages and the Normal Distribution -- 5.7 Introduction to z Scores -- 5.7.1 z Score Calculation -- 5.7.2 Basics of z Scores -- 5.7.3 Uses of z Scores -- 5.8 z Scores and the Normal Distribution -- 5.8.1 Problems About Percentages of Cases -- 5.8.2 Reminders and Cautions -- 5.9 Chapter Summary.

5.10 Problems and Questions -- 6. The Concept of Relationship and Relationship Between Categorical Variables -- 6.1 Chapter Overview -- 6.2 Definition of Relationship -- 6.3 Comments on Relationship -- 6.4 Contingency Tables and Categorical Variables -- 6.4.1 Reading a Contingency (Crosstabs) Table -- 6.4.2 Assessing Relationship Using a Contingency Table -- 6.5 Size of Association -- 6.6 Difference in Percentages (D%) -- 6.7 Qualitative Descriptors of Size of Association -- 6.8 Risk Ratio (RR) -- 6.9 Difference in Percentages or Risk Ratio? -- 6.10 Chapter Summary -- 6.11 Problems and Questions -- 7. The Odds Ratio and Other Measures for Categorical Variables -- 7.1 Chapter Overview -- 7.2 Odds Ratio -- 7.2.1 Basics and Formula -- 7.2.2 Interpretation -- 7.2.3 Advantages -- 7.3 Relationship in Contingency Tables Larger Than 2 × 2 -- 7.4 Directional Relationship -- 7.5 Measures of Directional Association Between Categorical Variables -- 7.6 Chapter Summary -- 7.7 Problems and Questions -- 8. Correlation and Regression -- 8.1 Chapter Overview -- 8.2 Positive and Negative Correlation -- 8.3 Scatterplots -- 8.4 Formula for the Correlation Coefficient, r -- 8.5 Understanding r -- 8.6 Interpretations Using r and z Scores -- 8.6.1 Predictions With z Scores -- 8.6.2 Predicted Change in Standard Deviation Units -- 8.7 Curvilinear Relationship -- 8.8 A Caution in Interpreting r -- 8.9 Regression -- 8.9.1 Regression Equation and Regression Line -- 8.9.2 Contrast Between r and B -- 8.10 Correlation for Nominal-Level and Ordinal-Level Variables -- 8.11 Chapter Summary -- 8.12 Problems and Questions -- 9. Standardized Mean Difference -- 9.1 Chapter Overview -- 9.2 Introduction to the Standardized Mean Difference -- 9.3 Graphical Interpretation of the Standardized Mean Difference -- 9.4 A Caution Regarding the Standardized Mean Difference.

9.5 More Measures of Differences Between Two Means -- 9.6 Differences Between Three or More Means -- 9.7 Chapter Summary -- 9.8 Problems and Questions -- 10. Research Design and Causality -- 10.1 Chapter Overview -- 10.2 Introduction to Causality -- 10.3 What Does "Cause" Mean in Social Science? -- 10.4 Confounding Variables -- 10.5 Experimental and Survey Designs -- 10.5.1 Experiments Versus Surveys -- 10.5.2 Random Assignment to Groups -- 10.6 Random Assignment and Causality -- 10.7 Chapter Summary -- 10.8 Problems and Questions -- 11. Controlling for Confounding Variables -- 11.1 Chapter Overview -- 11.2 Controlling for a Variable -- 11.2.1 Basic Concepts -- 11.2.2 Different Patterns Following Control -- 11.2.3 Initial Relationship Persists -- 11.2.4 Initial Relationship Weakens -- 11.2.5 Initial Relationship Disappears -- 11.3 Causal Models and Additional Considerations -- 11.4 Control for Multiple Variables and Causality -- 11.5 Interaction Effects -- 11.6 Chapter Summary -- 11.7 Problems and Questions -- PART II: INFERENTIAL STATISTICS AND DATA INTERPRETATION -- 12. An Introduction to Inferential Statistics -- 12.1 Chapter Overview -- 12.2 Descriptive Versus Inferential Statistics -- 12.3 Characteristics of Random Samples -- 12.4 The Advantage of Random Samples -- 12.5 Statistics and Parameters -- 12.6 Characteristics of Estimators -- 12.7 Sampling Error and Sampling Distributions -- 12.7.1 Concepts -- 12.7.2 Sampling Distribution of the Mean -- 12.8 Sample Size and the Sampling Distribution of X -- 12.9 Chapter Summary -- 12.10 Problems and Questions -- 13. Confidence Intervals for Means and Proportions -- 13.1 Chapter Overview -- 13.2 What Is a Confidence Interval? -- 13.3 Confidence Intervals for Means -- 13.3.1 Theory -- 13.3.2 Formulas and Computation -- 13.4 Confidence Intervals for Proportions and Percentages -- 13.4.1 Theory.

13.4.2 Formulas and Application -- 13.5 Five More Things to Know -- 13.6 Chapter Summary -- 13.7 Problems and Questions -- 14. The Logic of Statistical Significance Tests -- 14.1 Chapter Overview -- 14.2 Introduction to Significance Testing -- 14.3 Probability -- 14.3.1 Definition and Formula -- 14.3.2 Probability and the Normal Distribution -- 14.4 Null and Alternative Hypotheses -- 14.5 A Common Pattern for Hypothesis Pairs -- 14.6 Directional and Nondirectional Hypothesis Pairs -- 14.6.1 Definitions and Examples -- 14.6.2 Guidelines for Usage -- 14.7 Sampling Error and the Null Hypothesis -- 14.8 Statistical Significance Levels -- 14.9 Examples of Statistical Significance Testing -- 14.9.1 An Example in Which We Reject the Null -- 14.9.2 An Example in Which We Fail to Reject (Accept) the Null -- 14.9.3 More Interpretations of p -- 14.9.4 What Does It Mean to Reject the Null? -- 14.9.5 What Does It Mean to Fail to Reject (Accept) the Null? -- 14.10 Null and Alternative Hypotheses and Scientific Inquiry -- 14.11 What Is a Statistically Significant Result? -- 14.12 Chapter Summary -- 14.13 Problems and Questions -- 15. The Large Sample Test of the Mean and New Concepts -- 15.1 Chapter Overview -- 15.2 A Model for Hypothesis Testing -- 15.3 Assumptions of Statistical Significance Tests -- 15.3.1 Definition and Assumptions of the Large Sample Test of X -- 15.3.2 Assumptions Common to All Tests -- 15.4 The First Two Steps of the Hypothesis Testing Model -- 15.5 Statistical Tests and Sampling Distributions -- 15.6 Directional Versus Nondirectional Hypothesis Pairs -- 15.6.1 Overview -- 15.6.2 Nondirectional Hypothesis Pair -- 15.6.3 Directional Hypothesis Pair -- 15.7 Carrying Out the Significance Test Using the Sampling Distribution -- 15.8 Finishing the Example Using the Formula -- 15.8.1 Step 3: Carry Out the Test -- 15.8.2 Decision Rules.

15.8.3 Step 4: Make a Decision -- 15.9 Effect of Choice of Significance Level on Decision Making -- 15.10 Type I and Type II Errors -- 15.11 Two-Tailed Versus One-Tailed Tests -- 15.11.1 Carrying Out Our Example -- 15.11.2 Determining the Exact Value of the Study Sample Result (p) -- 15.12 More Decision Rules for the One-Tailed, Large Sample Test of X -- 15.13 Rejecting the Null and "Real" Things -- 15.14 Chapter Summary -- 15.15 Problems and Questions -- 16. Statistical Power and Selected Topics -- 16.1 Chapter Overview -- 16.2 Definition of Power -- 16.3 Sample Size and Power -- 16.4 Examples of How Sample Size Affects Power -- 16.4.1 The Parenting Skills Example -- 16.4.2 More Examples of Sample Size and Power -- 16.5 Factors Other Than Sample Size That Influence Power -- 16.5.1 Overview -- 16.5.2 Size of Relationship or Difference in the Population -- 16.5.3 Reduced Variability of Independent or Dependent Variable -- 16.5.4 Control for Third Variables -- 16.5.5 Significance Level -- 16.5.6 Directional Hypotheses and One-Tailed Tests -- 16.5.7 Statistical Significance Test -- 16.6 How Much Power is Enough? -- 16.7 How Large Should Sample Size Be? -- 16.8 Nonrandom Samples and Significance Tests -- 16.9 Reporting Statistical Significance -- 16.10 What Statistical Significance Is (And Is Not) -- 16.11 Chapter Summary -- 16.12 Problems and Questions -- 17. The t Distribution and One-Sample Procedures for Means -- 17.1 Chapter Overview -- 17.2 Small Sample Size and Distributions -- 17.3 Degrees of Freedom -- 17.4 The Family of t Distributions -- 17.5 Confidence Intervals for Means for Small Samples (and Large) -- 17.6 Introduction to the One-Sample t Test -- 17.6.1 Assumptions, Hypothesis Pairs, and Formula -- 17.6.2 Decision Rules -- 17.7 Carrying Out the One-Sample t Test -- 17.8 Chapter Summary -- 17.9 Problems and Questions.

18. Independent Samples t Test and Dependent Samples t Test.