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For the first course in statistics, this basic, comprehensive introductory text covers topics in conventional order, starting with descriptive statistics and ending with inferential statistics.

Tabla de contenidos provista por Syndetics

• Preface(p. xv)
• Acknowledgments(p. xix)
• Glossary of Symbols(p. xxi)
• Part I Descriptive Statistics(p. 1)
• Chapter 1 Introduction(p. 3)
• Why Study Statistics?(p. 4)
• Descriptive and Inferential Statistics(p. 5)
• Populations, Samples, Parameters, and Statistics(p. 6)
• Measurement Scales(p. 6)
• Independent and Dependent Variables(p. 8)
• Sara's Study(p. 9)
• Summation Notation(p. 10)
• Summary(p. 16)
• Exercises(p. 17)
• Thought Questions(p. 20)
• Computer Exercises(p. 21)
• Bridge to SPSS(p. 21)
• Chapter 2 Frequency Distributions and Graphs(p. 23)
• The Purpose of Descriptive Statistics(p. 24)
• Regular Frequency Distributions(p. 25)
• Cumulative Frequency Distributions(p. 26)
• Grouped Frequency Distributions(p. 27)
• Graphic Representations(p. 30)
• Shapes of Frequency Distributions(p. 35)
• Summary(p. 37)
• Exercises(p. 38)
• Thought Questions(p. 39)
• Computer Exercises(p. 40)
• Bridge to SPSS(p. 40)
• Chapter 3 Transformed Scores I: Percentiles(p. 42)
• Interpreting a Raw Score(p. 43)
• Definition of Percentile and Percentile Rank(p. 43)
• Computational Procedures(p. 44)
• Deciles, Quartiles, and the Median(p. 52)
• Summary(p. 52)
• Exercises(p. 53)
• Thought Questions(p. 54)
• Computer Exercises(p. 54)
• Bridge to SPSS(p. 54)
• Chapter 4 Measures of Central Tendency(p. 56)
• Introduction(p. 57)
• The Mean(p. 58)
• The Median(p. 64)
• The Mode(p. 66)
• Summary(p. 66)
• Exercises(p. 67)
• Thought Questions(p. 67)
• Computer Exercises(p. 68)
• Bridge to SPSS(p. 68)
• Chapter 5 Measures of Variability(p. 69)
• The Concept of Variability(p. 70)
• The Range(p. 72)
• The Semi-Interquartile Range(p. 73)
• The Standard Deviation and Variance(p. 74)
• Summary(p. 80)
• Exercises(p. 82)
• Thought Questions(p. 83)
• Computer Exercises(p. 83)
• Bridge to SPSS(p. 84)
• Chapter 6 Additional Techniques for Describing Batches of Data(p. 85)
• Numerical Summaries(p. 86)
• Graphic Summaries(p. 88)
• Summary(p. 91)
• Exercises(p. 91)
• Thought Questions(p. 92)
• Computer Exercises(p. 92)
• Bridge to SPSS(p. 92)
• Chapter 7 Transformed Scores II: z and T Scores(p. 94)
• Interpreting a Raw Score(p. 95)
• Rules for Changing X and [sigma](p. 96)
• Standard Scores (z Scores)(p. 98)
• T Scores and SAT Scores(p. 100)
• IQ Scores(p. 102)
• Summary(p. 103)
• Exercises(p. 104)
• Thought Questions(p. 106)
• Computer Exercises(p. 106)
• Bridge to SPSS(p. 106)
• Chapter 8 The Normal Distribution(p. 108)
• Introduction(p. 109)
• Score Distributions(p. 110)
• Parameters of the Normal Distribution(p. 111)
• Tables of the Standard Normal Distribution(p. 111)
• Characteristics of the Normal Curve(p. 112)
• Illustrative Examples(p. 113)
• Summary(p. 119)
• Exercises(p. 120)
• Thought Questions(p. 121)
• Computer Exercises(p. 121)
• Bridge to SPSS(p. 121)
• Part II Basic Inferential Statistics(p. 123)
• Chapter 9 Introduction to Statistical Inference(p. 125)
• Introduction(p. 126)
• The Goals of Inferential Statistics(p. 127)
• Sampling Distributions(p. 128)
• The Standard Error of the Mean(p. 132)
• The z Score for Sample Means(p. 135)
• Null Hypothesis Testing(p. 137)
• Assumptions Required by the Statistical Test for the Mean of a Single Population(p. 144)
• Summary(p. 144)
• Exercises(p. 146)
• Thought Questions(p. 148)
• Computer Exercises(p. 149)
• Bridge to SPSS(p. 149)
• Chapter 10 The One-Sample t Test and Interval Estimation(p. 150)
• The Statistical Test for the Mean of a Single Population When [sigma] Is Not Known: The t Distributions(p. 151)
• Interval Estimation(p. 155)
• The Standard Error of a Proportion(p. 159)
• Summary(p. 162)
• Exercises(p. 164)
• Thought Questions(p. 165)
• Computer Exercises(p. 166)
• Bridge to SPSS(p. 166)
• Chapter 11 Testing Hypotheses about the Difference between the Means of Two Populations(p. 167)
• The Standard Error of the Difference(p. 169)
• Estimating the Standard Error of the Difference(p. 173)
• The t Test for Two Sample Means(p. 174)
• Confidence Intervals for the Difference of Two Population Means(p. 177)
• Using the t Test for Two Sample Means: Some General Considerations(p. 179)
• Measuring Size of an Effect(p. 181)
• The t Test for Matched Samples(p. 182)
• Summary(p. 188)
• Exercises(p. 191)
• Thought Questions(p. 193)
• Computer Exercises(p. 195)
• Bridge to SPSS(p. 195)
• Chapter 12 Linear Correlation and Prediction(p. 197)
• Introduction(p. 198)
• Describing the Linear Relationship between Two Variables(p. 201)
• Interpreting the Magnitude of a Pearson r(p. 210)
• When Is It Important That Pearson's r be Large?(p. 212)
• Testing the Significance of the Correlation Coefficient(p. 214)
• Prediction and Linear Regression(p. 217)
• Measuring Prediction Error: The Standard Error of Estimate(p. 225)
• Summary(p. 228)
• Exercises(p. 230)
• Thought Questions(p. 233)
• Computer Exercises(p. 234)
• Bridge to SPSS(p. 235)
• Appendix Equivalence of the Various Formulas for r(p. 236)
• Chapter 13 The Connection between Correlation and the t Test(p. 241)
• Introduction(p. 242)
• The Point-Biserial Correlation Coefficient(p. 243)
• The Proportion of Variance Accounted For in Your Samples(p. 246)
• Estimating the Proportion of Variance Accounted For in the Population(p. 247)
• Summary(p. 249)
• Exercises(p. 250)
• Thought Questions(p. 251)
• Computer Exercises(p. 252)
• Bridge to SPSS(p. 252)
• Chapter 14 Introduction to Power Analysis(p. 255)
• Introduction(p. 256)
• Concepts of Power Analysis(p. 257)
• The Test of the Mean of a Single Population(p. 259)
• The Significance Test of the Proportion of a Single Population(p. 264)
• The Significance Test of a Pearson r(p. 266)
• Testing the Difference between Independent Means(p. 267)
• Testing the Difference between the Means of Two Matched Populations(p. 272)
• Choosing a Value for d for a Power Analysis Involving Independent Means(p. 273)
• Using Power Analysis to Interpret the Results of Null Hypothesis Tests(p. 275)
• Summary(p. 277)
• Exercises(p. 281)
• Thought Questions(p. 283)
• Computer Exercises(p. 284)
• Bridge to SPSS(p. 284)
• Part III Analysis of Variance Methods(p. 287)
• Chapter 15 One-Way Analysis of Variance(p. 289)
• Introduction(p. 290)
• The General Logic of ANOVA(p. 291)
• Computational Procedures(p. 295)
• Comparing the One-Way ANOVA with the t Test(p. 301)
• A Simplified ANOVA Formula for Equal Sample Sizes(p. 302)
• Effect Size for the One-Way ANOVA(p. 305)
• Summary(p. 306)
• Exercises(p. 309)
• Thought Questions(p. 310)
• Computer Exercises(p. 311)
• Bridge to SPSS(p. 312)
• Appendix Proof That the Total Sum of Squares Is Equal to the Sum of the Between-Group and the Within-Group Sum of Squares(p. 312)
• Chapter 16 Multiple Comparisons(p. 314)
• Introduction(p. 315)
• Fisher's Protected t Tests(p. 316)
• Tukey's Honestly Significant Difference (HSD)(p. 319)
• Other Multiple Comparison Procedures(p. 322)
• Planned and Complex Comparisons(p. 324)
• Summary(p. 327)
• Exercises(p. 328)
• Thought Questions(p. 329)
• Computer Exercises(p. 330)
• Bridge to SPSS(p. 330)
• Chapter 17 Introduction to Factorial Design: Two-Way Analysis of Variance(p. 332)
• Introduction(p. 333)
• Computational Procedures(p. 334)
• The Meaning of Interaction(p. 342)
• Following Up a Significant Interaction(p. 346)
• Summary(p. 349)
• Exercises(p. 352)
• Thought Questions(p. 355)
• Computer Exercises(p. 356)
• Bridge to SPSS(p. 358)
• Chapter 18 Repeated-Measures ANOVA(p. 359)
• Introduction(p. 360)
• Calculating the One-Way RM ANOVA(p. 360)
• Rationale for the RM ANOVA Error Term(p. 363)
• Assumptions of the RM ANOVA(p. 365)
• The RM versus RB Design: An Introduction to Issues of Experimental Design(p. 367)
• The Two-Way Mixed Design(p. 371)
• Summary(p. 377)
• Exercises(p. 382)
• Thought Questions(p. 384)
• Computer Exercises(p. 384)
• Bridge to SPSS(p. 384)
• Part IV Nonparametric Statistics(p. 387)
• Chapter 19 Introduction to Probability and Nonparametric Methods(p. 389)
• Introduction(p. 390)
• Probability(p. 391)
• The Binomial Distribution(p. 394)
• The Sign Test for Matched Samples(p. 400)
• Summary(p. 402)
• Exercises(p. 403)
• Thought Questions(p. 405)
• Computer Exercises(p. 406)
• Bridge to SPSS(p. 406)
• Chapter 20 Chi Square Tests(p. 409)
• Chi Square and Goodness of Fit: One-Variable Problems(p. 410)
• Chi Square as a Test of Independence: Two-Variable Problems(p. 414)
• Measures of Strength of Association in Two-Variable Tables(p. 420)
• Summary(p. 423)
• Exercises(p. 425)
• Thought Questions(p. 427)
• Computer Exercises(p. 428)
• Bridge to SPSS(p. 429)
• Chapter 21 Tests for Ordinal Data(p. 432)
• Introduction(p. 433)
• The Difference between the Locations of Two Independent Samples: The Rank-Sum Test(p. 436)
• Differences among the Locations of Two or More Independent Samples: The Kruskal-Wallis H Test(p. 440)
• The Difference between the Locations of Two Matched Samples: The Wilcoxon Test(p. 444)
• The Relationship between Two Ranked Variables: The Spearman Rank-Order Correlation(p. 449)
• Summary(p. 452)
• Exercises(p. 455)
• Thought Questions(p. 461)
• Computer Exercises(p. 461)
• Bridge to SPSS(p. 462)
• Appendix(p. 465)
• Statistical Tables(p. 467)
• Answer Key(p. 483)
• Data from Sara's Experiment(p. 496)
• Glossary of Terms(p. 499)
• References(p. 506)
• Index(p. 507)

Notas de autor provistas por Syndetics

Joan Welkowitz, PhD, was a Professor of Psychology at New York University. She directed the clinical program for ten years, and taught courses in methodology and statistics at both the graduate and undergraduate levels for more than twenty-five years. Barry H. Cohen, PhD, is the Director of the master′s program in psychology at New York University, where he has been teaching statistics for more than twenty years. He is the author or coauthor of two other successful statistics books also from Wiley- Explaining Psychological Statistics, Second Edition and Essentials of Statistics for the Social and Behavioral Sciences with R. Brooke Lea. Robert B. Ewen, PhD, teaches advanced placement psychology at Gulliver Preparatory School in Miami, Florida. He previously taught statistics for eight years as an associate professor at New York University. He is also the author of a successful college text on theories of personality that is currently in its sixth edition.