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  • Introductory Statistics for the Behavioral Sciences, 7th Edition
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Introductory Statistics for the Behavioral Sciences, 7th Edition 요약정보 및 구매

Textbook

저자 : Joan Welkowitz, Barry H. Cohen, R. Brooke Lea

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위시리스트0
시중가격 69,000원
판매가격 65,000원
출판사 Wiely
발행일2011
ISBN 9780470907764
페이지576 Pages
언어 ENG
배송비결제 주문시 결제

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  • Introductory Statistics for the Behavioral Sciences, 7th Edition
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    DESCRIPTION

    A comprehensive and user-friendly introduction to statistics for behavioral science students—revised and updated

    Refined over seven editions by master teachers, this book gives instructors and students alike clear examples and carefully crafted exercises to support the teaching and learning of statistics for both manipulating and consuming data.

    One of the most popular and respected statistics texts in the behavioral sciences, the Seventh Edition of Introductory Statistics for the Behavioral Sciences has been fully revised. The new edition presents all the topics students in the behavioral sciences need in a uniquely accessible and easy-to-understand format, aiding in the comprehension and implementation of the statistical analyses most commonly used in the behavioral sciences.

     

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    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 μ and σ 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 σ 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 μ1 − μ2 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

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