Introductory statistics for the behavioral sciences

Preface xv    Acknowledgments xix     Glossary of Symbols xxi     Part I Descriptive Statistics 1     Chapter 1 Introduction 3     Why Study Statistics? 4     Descriptive and Inferential Statistics 5     Populations, Samples, Parameters, and Statistics 6     Measurement Scales 7     Independent and Dependent Variables 10     Summation Notation 12     Ihno   s Study 16     Summary 18     Exercises 19     Thought Questions 23     Computer Exercises 23     Bridge to SPSS 24     Chapter 2 Frequency Distributions and Graphs 26     The Purpose of Descriptive Statistics 27     Regular Frequency Distributions 28     Cumulative Frequency Distributions 30     Grouped Frequency Distributions 31     Real and Apparent Limits 33     Interpreting a Raw Score 34     Definition of Percentile Rank and Percentile 34     Computational Procedures 35     Deciles, Quartiles, and the Median 38     Graphic Representations 39     Shapes of Frequency Distributions 43     Summary 45     Exercises 47     Thought Questions 49     Computer Exercises 49     Bridge to SPSS 50     Chapter 3 Measures of Central Tendency and Variability 53     Introduction 54     The Mode 56     The Median 56     The Mean 58     The Concept of Variability 62     The Range 65     The Standard Deviation and Variance 66     Summary 73     Exercises 75     Thought Questions 76     Computer Exercises 77     Bridge to SPSS 78     Chapter 4 Standardized Scores and the Normal Distribution 81     Interpreting a Raw Score Revisited 82     Rules for Changing    and    84     Standard Scores (z Scores) 85     T Scores, SAT Scores, and IQ Scores 88     The Normal Distribution 90     Table of the Standard Normal Distribution 93     Illustrative Examples 95     Summary 101     Exercises 103     Thought Questions 105     Computer Exercises 106     Bridge to SPSS 106     Part II Basic Inferential Statistics 109     Chapter 5 Introduction to Statistical Inference 111     Introduction 113     The Goals of Inferential Statistics 114     Sampling Distributions 114     The Standard Error of the Mean 119     The z Score for Sample Means 122     Null Hypothesis Testing 124     Assumptions Required by the Statistical Test for the Mean of a Single Population 132     Summary 133     Exercises 135     Thought Questions 137     Computer Exercises 138     Bridge to SPSS 138     Appendix: The Null Hypothesis Testing Controversy 139     Chapter 6 The One-Sample t Test and Interval Estimation 142     Introduction 143     The Statistical Test for the Mean of a Single Population When    Is Not Known: The t Distributions 144     Interval Estimation 148     The Standard Error of a Proportion 152     Summary 155     Exercises 156     Thought Questions 157     Computer Exercises 158     Bridge to SPSS 158     Chapter 7 Testing Hypotheses About the Difference Between the Means of Two Populations 160     The Standard Error of the Difference 162     Estimating the Standard Error of the Difference 166     The t Test for Two Sample Means 167     Confidence Intervals for   1       2 172     The Assumptions Underlying the Proper Use of the t Test for Two Sample Means 175     Measuring the Size of an Effect 176     The t Test for Matched Samples 178     Summary 185     Exercises 187     Thought Questions 190     Computer Exercises 191     Bridge to SPSS 191     Chapter 8 Nonparametric Tests for the Difference Between Two Means 194     Introduction 195     The Difference Between the Locations of Two Independent Samples: The Rank-Sum Test 199     The Difference Between the Locations of Two Matched Samples: The Wilcoxon Test 205     Summary 210     Exercises 212     Thought Questions 215     Computer Exercises 216     Bridge to SPSS 216     Chapter 9 Linear Correlation 218     Introduction 219     Describing the Linear Relationship Between Two Variables 222     Interpreting the Magnitude of a Pearson r 229     When Is It Important That Pearson   s r Be Large? 234     Testing the Significance of the Correlation Coefficient 236     The Relationship Between Two Ranked Variables: The Spearman Rank-Order Correlation Coefficient 239     Summary 242     Exercises 244     Thought Questions 247     Computer Exercises 248     Bridge to SPSS 248     Appendix: Equivalence of the Various Formulas for r 251     Chapter 10 Prediction and Linear Regression 253     Introduction 254     Using Linear Regression to Make Predictions 254     Measuring Prediction Error: The Standard Error of Estimate 263     The Connection Between Correlation and the t Test 265     Estimating the Proportion of Variance Accounted for in the Population 271     Summary 273     Exercises 275     Thought Questions 277     Computer Exercises 277     Bridge to SPSS 278     Chapter 11 Introduction to Power Analysis 281     Introduction 282     Concepts of Power Analysis 283     The Significance Test of the Mean of a Single Population 285     The Significance Test of the Proportion of a Single Population 290     The Significance Test of a Pearson r 292     Testing the Difference Between Independent Means 293     Testing the Difference Between the Means of Two Matched Populations 297     Choosing a Value for d for a Power Analysis Involving Independent Means 299     Using Power Analysis Concepts to Interpret the Results of Null Hypothesis Tests 301     Summary 304     Exercises 306     Thought Questions 308     Computer Exercises 309     Bridge to SPSS 310     Part III Analysis of Variance Methods 313     Chapter 12 One-Way Analysis of Variance 315     Introduction 317     The General Logic of ANOVA 318     Computational Procedures 321     Testing the F Ratio for Statistical Significance 326     Calculating the One-Way ANOVA From Means and Standard Deviations 328     Comparing the One-Way ANOVA With the t Test 329     A Simplified ANOVA Formula for Equal Sample Sizes 330     Effect Size for the One-Way ANOVA 331     Some Comments on the Use of ANOVA 333     A Nonparametric Alternative to the One-Way ANOVA: The Kruskal-Wallis H Test 336     Summary 339     Exercises 343     Thought Questions 346     Computer Exercises 346     Bridge to SPSS 346     Appendix: Proof That the Total Sum of Squares Is Equal to the Sum of the Between-Group and the Within-Group Sum of Squares 348     Chapter 13 Multiple Comparisons 349     Introduction 350     Fisher   s Protected t Tests and the Least Significant Difference (LSD) 351     Tukey   s Honestly Significant Difference (HSD) 355     Other Multiple Comparison Procedures 360     Planned and Complex Comparisons 362     Nonparametric Multiple Comparisons: The Protected Rank-Sum Test 365     Summary 366     Exercises 368     Thought Questions 369     Computer Exercises 370     Bridge to SPSS 370     Chapter 14 Introduction to Factorial Design: Two-Way Analysis of Variance 372     Introduction 373     Computational Procedures 374     The Meaning of Interaction 384     Following Up a Significant Interaction 387     Measuring Effect Size in a Factorial ANOVA 390     Summary 392     Exercises 395     Thought Questions 398     Computer Exercises 399     Bridge to SPSS 399     Chapter 15 Repeated-Measures ANOVA 402     Introduction 403     Calculating the One-Way RM ANOVA 403     Rationale for the RM ANOVA Error Term 408     Assumptions and Other Considerations Involving the RM ANOVA 408     The RM Versus RB Design: An Introduction to the Issues of Experimental Design 411     The Two-Way Mixed Design 415     Summary 423     Exercises 428     Thought Questions 430     Computer Exercises 430     Bridge to SPSS 431     Part IV Nonparametric Statistics for Categorical Data 435     Chapter 16 Probability of Discrete Events and the Binomial Distribution 437     Introduction 438     Probability 439     The Binomial Distribution 442     The Sign Test for Matched Samples 448     Summary 450     Exercises 451     Thought Questions 453     Computer Exercises 453     Bridge to SPSS 454     Chapter 17 Chi-Square Tests 457     Chi Square and the Goodness of Fit: One-Variable Problems 458     Chi Square as a Test of Independence: Two-Variable Problems 464     Measures of Strength of Association in Two-Variable Tables 470     Summary 472     Exercises 474     Thought Questions 476     Computer Exercises 477     Bridge to SPSS 478     Appendix 481     Statistical Tables 483     Answers to Odd-Numbered Exercises 499     Data From Ihno   s Experiment 511     Glossary of Terms 515     References 525     Index 527