Statistics for the Behavioral Sciences

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The engaging Third Edition of Statistics for the Behavioral Sciences shows students that statistics can be understandable, interesting, and relevant to their daily lives. Using a conversational tone, award-winning teacher and author Gregory J. Privitera speaks to the reader as researcher when covering statistical theory, computation, and application. Robust pedagogy allows students to continually check their comprehension and hone their skills when working through carefully developed problems and exercises that include current research and seamless integration of SPSS. This edition will not only prepare students to be lab-ready, but also give them the confidence to use statistics to summarize data and make decisions about behavior.

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About the AuthorAcknowledgmentsPreface to the InstructorTo the Student-How to Use SPSS With This BookPART I. INTRODUCTION AND DESCRIPTIVE STATISTICSChapter 1. Introduction to Statistics 1.1 The Use of Statistics in Science 1.2 Descriptive and Inferential 1.3 Research Methods and Statistics 1.4 Scales of Measurement 1.5 Types of Variables for Which Data Are Measured 1.6 Research in Focus: Evaluating Data and Scales of Measurement 1.7 SPSS in Focus: Entering and Defining Variables Chapter Summary Key Terms End-of-Chapter ProblemsChapter 2. Summarizing Data: Frequency Distributions in Tables and Graphs 2.1 Why Summarize Data? 2.2 Frequency Distributions for Grouped Data 2.3 Identifying Percentile Points and Percentile Ranks 2.4 SPSS in Focus: Frequency Distributions for Quantitative Data 2.5 Frequency Distributions for Ungrouped Data 2.6 Research in Focus: Summarizing Demographic Information 2.7 SPSS in Focus: Frequency Distributions for Categorical Data 2.8 Pictorial Frequency Distributions 2.9 Graphing Distributions: Continuous Data 2.10 Graphing Distributions: Discrete and Categorical Data 2.11 Research in Focus: Frequencies and Percents 2.12 SPSS in Focus: Histograms, Bar Charts, and Pie Charts Chapter Summary Key Terms End-of-Chapter ProblemsChapter 3. Summarizing Data: Central Tendency 3.1 Introduction to Central Tendency 3.2 Measures of Central Tendency 3.3 Characteristics of the Mean 3.4 Choosing an Appropriate Measure of Central Tendency 3.5 Research in Focus: Describing Central Tendency 3.6 SPSS in Focus: Mean, Median, and Mode Chapter Summary Key Terms End-of-Chapter ProblemsChapter 4. Summarizing Data: Variability 4.1 Measuring Variability 4.2 The Range 4.3 Research in Focus: Reporting the Range 4.4 Quartiles and Interquartiles 4.5 The Variance 4.6 Explaining Variance for Populations and Samples 4.7 The Computational Formula for Variance 4.8 The Standard Deviation 4.9 What Does the Standard Deviation Tell Us? 4.10 Characteristics of the Standard Deviation 4.11 SPSS in Focus: Range, Variance, and Standard Deviation Chapter Summary Key Terms End-of-Chapter ProblemsPART II. PROBABILITY AND THE FOUNDATIONS OF INFERENTIAL STATISTICSChapter 5. Probability 5.1 Introduction to Probability 5.2 Calculating Probability 5.3 Probability and Relative Frequency 5.4 The Relationship Between Multiple Outcomes 5.5 Conditional Probabilities and Bayes's Theorem 5.6 SPSS in Focus: Probability Tables 5.7 Probability Distributions 5.8 The Mean of a Probability Distribution and Expected Value 5.9 Research in Focus: When Are Risks Worth Taking? 5.10 The Variance and Standard Deviation of a Probability Distribution 5.11 Expected Value and the Binomial Distribution 5.12 A Final Thought on the Likelihood of Random Behavioral Outcomes Chapter Summary Key Terms End-of-Chapter ProblemsChapter 6. Probability, Normal Distributions, and z Scores 6.1 The Normal Distribution in Behavioral Science 6.2 Characteristics of the Normal Distribution 6.3 Research in Focus: The Statistical Norm 6.4 The Standard Normal Distribution 6.5 The Unit Normal Table: A Brief Introduction 6.6 Locating Proportions 6.7 Locating Scores 6.8 SPSS in Focus: Converting Raw Scores to Standard z Scores 6.9 Going From Binomial to Normal 6.10 The Normal Approximation to the Binomial Distribution Chapter Summary Key Terms End-of-Chapter ProblemsChapter 7. Probability and Sampling Distributions 7.1 Selecting Samples From Populations 7.2 Selecting a Sample: Who's In and Who's Out? 7.3 Sampling Distributions: The Mean 7.4 Sampling Distributions: The Variance 7.5 The Standard Error of the Mean 7.6 Factors That Decrease Standard Error 7.7 SPSS in Focus: Estimating the Standard Error of the Mean 7.8 APA in Focus: Reporting the Standard Error 7.9 Standard Normal Transformations With Sampling Distributions Chapter Summary Key Terms End-of-Chapter ProblemsPART III. MAKING INFERENCES ABOUT ONE OR TWO MEANSChapter 8. Hypothesis Testing: Significance, Effect Size, and Power 8.1 Inferential Statistics and Hypothesis Testing 8.2 Four Steps to Hypothesis Testing 8.3 Hypothesis Testing and Sampling Distributions 8.4 Making a Decision: Types of Error 8.5 Testing for Significance: Examples Using the z Test 8.6 Research in Focus: Directional Versus Nondirectional Tests 8.7 Measuring the Size of an Effect: Cohen's d 8.8 Effect Size, Power, and Sample Size 8.9 Additional Factors That Increase Power 8.10 SPSS in Focus: A Preview for Chapters 9 to 18 8.11 APA in Focus: Reporting the Test Statistic and Effect Size Chapter Summary Key Terms End-of-Chapter ProblemsChapter 9. Testing Means: One-Sample and Two-Independent- Sample t Tests 9.1 Going From z to t 9.2 The Degrees of Freedom 9.3 Reading the t Table 9.4 One-Sample t Test 9.5 Effect Size for the One-Sample t Test 9.6 SPSS in Focus: One-Sample t Test 9.7 Two-Independent-Sample t Test 9.8 Effect Size for the Two-Independent- Sample t Test 9.9 SPSS in Focus: Two-Independent- Sample t Test 9.10 APA in Focus: Reporting the t Statistic and Effect Size Chapter Summary Key Terms End-of-Chapter ProblemsChapter 10. Testing Means: The Related-Samples t Test 10.1 Related and Independent Samples 10.2 Introduction to the Related-Samples t Test 10.3 The Related-Samples t Test: Repeated-Measures Design 10.4 SPSS in Focus: The Related-Samples t Test 10.5 The Related-Samples t Test: Matched-Pairs Design 10.6 Measuring Effect Size for the Related-Samples t Test 10.7 Advantages for Selecting Related Samples 10.8 APA in Focus: Reporting the t Statistic and Effect Size for Related Samples Chapter Summary Key Terms End-of-Chapter ProblemsChapter 11. Estimation and Confidence Intervals 11.1 Point Estimation and Interval Estimation 11.2 The Process of Estimation 11.3 Estimation for the One-Sample z Test 11.4 Estimation for the One-Sample t Test 11.5 SPSS in Focus: Confidence Intervals for the One-Sample t Test 11.6 Estimation for the Two-Independent-Sample t Test 11.7 SPSS in Focus: Confidence Intervals for the Two-Independent- Sample t Test 11.8 Estimation for the Related-Samples t Test 11.9 SPSS in Focus: Confidence Intervals for the Related-Samples t Test 11.10 Characteristics of Estimation: Precision and Certainty 11.11 APA in Focus: Reporting Confidence Intervals Chapter Summary Key Terms End-of-Chapter ProblemsPART IV. MAKING INFERENCES ABOUT THE VARIABILITY OF TWO OR MORE MEANSChapter 12. Analysis of Variance: One-Way Between- Subjects Design 12.1 Analyzing Variance for Two or More Groups 12.2 An Introduction to Analysis of Variance 12.3 Sources of Variation and the Test Statistic 12.4 Degrees of Freedom 12.5 The One-Way Between-Subjects ANOVA 12.6 What Is the Next Step? 12.7 Post Hoc Comparisons 12.8 SPSS in Focus: The One-Way Between-Subjects ANOVA 12.9 Measuring Effect Size 12.10 APA in Focus: Reporting the F Statistic, Significance, and Effect Size Chapter Summary Key Terms End-of-Chapter ProblemsChapter 13. Analysis of Variance: One-Way Within-Subjects (Repeated-Measures) Design 13.1 Observing the Same Participants Across Groups 13.2 Sources of Variation and the Test Statistic 13.3 Degrees of Freedom 13.4 The One-Way Within-Subjects ANOVA 13.5 Post Hoc Comparisons: Bonferroni Procedure 13.6 SPSS in Focus: The One-Way Within-Subjects ANOVA 13.7 Measuring Effect Size 13.8 The Within-Subjects Design: Consistency and Power 13.9 APA in Focus: Reporting the F Statistic, Significance, and Effect Size Chapter Summary Key Terms End-of-Chapter ProblemsChapter 14. Analysis of Variance: Two-Way Between-Subjects Factorial Design 14.1 Observing Two Factors at the Same Time 14.2 New Terminology and Notation 14.3 Designs for the Two-Way ANOVA 14.4 Describing Variability: Main Effects 14.5 The Two-Way Between-Subjects ANOVA 14.6 Analyzing Main Effects and Interactions 14.7 Measuring Effect Size 14.8 SPSS in Focus: The Two-Way Between-Subjects ANOVA 14.9 APA in Focus: Reporting Main Effects, Interactions, and Effect Size Chapter Summary Key Terms End-of-Chapter ProblemsPART V. MAKING INFERENCES ABOUT PATTERNS, FREQUENCIES, AND ORDINAL DATAChapter 15. Correlation 15.1 The Structure of a Correlational Design 15.2 Describing a Correlation 15.3 Pearson Correlation Coefficient 15.4 SPSS in Focus: Pearson Correlation Coefficient 15.5 Assumptions of Tests for Linear Correlations 15.6 Limitations in Interpretation: Causality, Outliers, and Restrictions of Range 15.7 Alternative to Pearson r: Spearman Correlation Coefficient 15.8 SPSS in Focus: Spearman Correlation Coefficient 15.9 Alternative to Pearson r: Point-Biserial Correlation Coefficient 15.10 SPSS in Focus: Point-Biserial Correlation Coefficient 15.11 Alternative to Pearson r: Phi Correlation Coefficient 15.12 SPSS in Focus: Phi Correlation Coefficient 15.13 APA in Focus: Reporting Correlations Chapter Summary Key Terms End-of-Chapter ProblemsChapter 16. Linear Regression and Multiple Regression 16.1 From Relationships to Predictions 16.2 Fundamentals of Linear Regression 16.3 What Makes the Regression Line the Best-Fitting Line? 16.4 The Slope and y-Intercept of a Straight Line 16.5 Using the Method of Least Squares to Find the Best Fit 16.6 Using Analysis of Regression to Determine Significance 16.7 SPSS in Focus: Analysis of Regression 16.8 Using the Standard Error of Estimate to Measure Accuracy 16.9 Introduction to Multiple Regression 16.10 Computing and Evaluating Significance for Multiple Regression 16.11 The ss Coefficient for Multiple Regression 16.12 Evaluating Significance for the Relative Contribution of Each Predictor Variable 16.13 SPSS in Focus: Multiple Regression Analysis 16.14 APA in Focus: Reporting Regression Analysis Chapter Summary Key Terms End-of-Chapter ProblemsChapter 17. Nonparametric Tests: Chi-Square Tests 17.1 Tests for Nominal Data 17.2 The Chi-Square Goodness-of-Fit Test 17.3 SPSS in Focus: The Chi-Square Goodness-of-Fit Test 17.4 Interpreting the Chi-Square Goodness-of-Fit Test 17.5 Independent Observations and Expected Frequency Size 17.6 The Chi-Square Test for Independence 17.7 The Relationship Between Chi-Square and the Phi Coefficient 17.8 Measures of Effect Size 17.9 SPSS in Focus: The Chi-Square Test for Independence 17.10 APA in Focus: Reporting the Chi-Square Test Chapter Summary Key Terms End-of-Chapter ProblemsChapter 18. Nonparametric Tests: Tests for Ordinal Data 18.1 Tests for Ordinal Data 18.2 The Sign Test 18.3 SPSS in Focus: The Related-Samples Sign Test 18.4 The Wilcoxon Signed-Ranks T Test 18.5 SPSS in Focus: The Wilcoxon Signed-Ranks T Test 18.6 The Mann-Whitney U Test 18.7 SPSS in Focus: The Mann-Whitney U Test 18.8 The Kruskal-Wallis H Test 18.9 SPSS in Focus: The Kruskal-Wallis H Test 18.10 The Friedman Test 18.11 SPSS in Focus: The Friedman Test 18.12 APA in Focus: Reporting Nonparametric Tests Chapter Summary Key Terms End-of-Chapter ProblemsAfterword: A Final Thought on the Role of Statistics in Research MethodsAppendix A. Basic Math Review and Summation Notation A.1 Positive and Negative Numbers A.2 Addition A.3 Subtraction A.4 Multiplication A.5 Division A.6 Fractions A.7 Decimals and Percents A.8 Exponents and Roots A.9 Order of Computation A.10 Equations: Solving for x A.11 Summation Notation Key Terms Review ProblemsAppendix B. SPSS General Instructions GuideAppendix C. Statistical Tables Table C.1 The Unit Normal Table Table C.2 Critical Values for the t Distribution Table C.3 Critical Values for the F Distribution Table C.4 The Studentized Range Statistic (q) Table C.5 Critical Values for the Pearson Correlation Table C.6 Critical Values for the Spearman Correlation Table C.7 Critical Values of Chi-Square (c2) Table C.8 Distribution of Binomial Probabilities When p = .50 Table C.9 Wilcoxon Signed-Ranks T Critical Values Table C.10A Critical Values of the Mann-Whitney U for a = .05 Table C.10B Critical Values of the Mann-Whitney U for a = .01Appendix D. Chapter Solutions for Even-Numbered ProblemsGlossaryReferencesIndex

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