Statistics for the behavioral sciences

목차 (Table of Contents)

• CONTENTS
• PREFACE = xx
• CHAPTER 1 The Language of Statistics = 1
• What Is Statistics? = 2
• Why Study Statistics? = 2
• Personal Reasons = 2
• Professional Reasons = 3
• Our Goals = 4
• Statistics as a Second Language = 5
• What You Need to Use This Book Successfully = 5
• Summary = 7
• Exercises = 7
• PART 1 Descriptive Statistics = 9
• CHAPTER 2 Definitions and Scaling = 11
• Statistics : Some Basic Vocabulary = 12
• Variable = 12
• Population and Parameters = 13
• Sample, Statistic, and Sampling = 13
• Scales of Measurement = 15
• The Nominal Scale = 16
• The Ordinal Scale = 16
• The Interval Scale = 17
• The Ratio Scale = 18
• Two Basic Uses of Statistics = 19
• Summary = 20
• Exercises = 20
• CHAPTER 3 The Frequency Distribution = 22
• Defining the Frequency Distribution = 23
• Continuous Variables and Discrete Variables = 25
• Real Limits and Apparent Limits = 28
• Frequency Distributions = 29
• Summary = 32
• Exercises = 32
• CHAPTER 4 Graphing Data = 35
• Rules for Graphing = 35
• The Frequency Polygon = 37
• AComparison ofDistributions Usingthe Percentageor Relative Frequency Polygon = 39
• Shapes of Frequency Polygons = 42
• The Cumulative Frequency( or Cumulative Percentage) Polygon = 44
• The Histogram = 48
• The Bar Graph = 49
• The Stem-and-Leaf Plot = 50
• Comparing Groups With the Stem-and-Leaf Plot = 52
• The Line Graph = 53
• Summary = 57
• Exercises = 58
• CHAPTER 5 Measures of Central Tendency = 63
• The Mode = 65
• The Median = 66
• Locating the Median by the Counting Method : Even Number of Scores = 67
• Locating the Median by the Counting Method : Odd Number ofScores = 69
• The Mean, or Arithmetic Average = 72
• Rounding Conventions = 74
• The Mean as a Balancing Point = 75
• Comparing Measures of Central Tendency = 80
• Positions of Measures of Central Tendency on a Frequency Polygon = 81
• Summary = 83
• Troubleshooting Your Computations = 84
• Exercises = 85
• CHAPTER 6 Measures of Dispersion and Standard Scores = 91
• The Range = 92
• The Average Deviation = 93
• The Variance and the Standard Deviation = 94
• The Variance = 94
• The Standard Deviation = 99
• Visualizing the Standard Deviation = 102
• Standard Scores(z Scores) = 105
• Summary = 109
• Troubleshooting Your Computations = 111
• Exercises = 112
• Review of Descriptive Statistics = 116
• PART 2 Inferential Statistics = 119
• CHAPTER 7 Probability = 121
• Thinking About Probability = 122
• Probability and the Individual = 123
• Theoretical Probability = 124
• Real-World Probability = 124
• Subjective Probability = 124
• Rules of Probability = 125
• The Addition Rule = 125
• The Multiplication Rule = 126
• More on Conditional Probability = 129
• Bayesian Statistics = 130
• The Binomial Probability Distribution = 132
• Summary = 135
• Exercises = 136
• CHAPTER 8 The Normal Distribution = 139
• Curves and Probability = 141
• Characteristics of the Normal Curve = 142
• Review of z Scores = 143
• Using the Normal Curve Table = 144
• Finding Areas Under the Curve = 147
• Finding the Percentile Rank of a Score = 147
• Finding the Percentage of the Normal Curve Above a Score = 150
• Finding Percentage Frequency = 151
• Finding an Area Between Two Scores = 153
• Probability an Areas Under the Curve = 156
• Brief Summary = 158
• Finding Scores Cutting Off Areas = 158
• Finding the Scores That Has a Particular Percentile Rank = 158
• Finding Deviant Scores = 160
• Probability and Deviant Scores = 162
• Brief Summary = 163
• Summary = 164
• Troubleshooting Your Computations = 165
• Exercises = 165
• CHAPTER 9 Confidence Intervals and Hypothesis Testing = 168
• The Sampling Distribution of Means = 169
• Estimation and Degrees of Freedom = 176
• Confidence Intervals = 178
• Interpretation Statement for a Confidence Interval = 182
• Another Confidence Interval Example = 183
• Understanding the Level of Confidence = 184
• Hypothesis Testing : One-Sample t Test = 184
• Seven-Step Procedure for Testing the Null Hypothesis = 190
• Directional Tests = 192
• Type I and Type Ⅱ Errors = 193
• The Power of a Statistical Test = 195
• Meta-Analysis = 197
• Should Hypothesis Testing Be Abandoned? = 198
• Summary = 199
• Troubleshooting Your Computations = 201
• Exercises = 202
• CHAPTER 10 Significance of the Difference Between Two Sample Means = 206
• The Sampling Distribution of the Differences Between Sample Means = 207
• Computing t : Independent Samples = 213
• One-Tailed Versus Two-Tailed Tests = 216
• Another Example of the t Test for Independent Samples = 217
• Assumptions of the Two-Sample t Test = 220
• Computing t : Dependent Samples = 221
• Obtaining Dependent Samples = 221
• The Direct Difference Method = 223
• Summary = 228
• Troubleshooting Your Computations = 229
• Exercises = 230
• CHAPTER 11 One-WayAnalysis of Variance With Post Hoc
• Comparisons = 237
• Between-Subjects ANOVA = 239
• Visualization of ANOVA Concepts = 240
• Measuring Variability : The Sum of Squares = 246
• Computing the Sums of Squares = 248
• A General Rule for Computing Sums of Squares = 250
• The Analysis of Variance Summary Table = 251
• Another Between-Subjects ANOVA Example = 256
• Post Hoc Comparisons = 259
• The Fisher LSD = 260
• Using the Fisher LSD = 261
• Another Fisher LSD Example = 263
• The Tukey HSD = 265
• Using the Tukey HSD = 266
• Repeated Measures ANOVA = 267
• Summary = 272
• Troubleshooting Your Computations = 274
• Exercises = 275
• CHAPTER 12 Two-Way Analysis of Variance = 280
• Main Effects and Effects of Interaction = 282
• Advantages of the Two-Factor Design = 285
• Logic of the Two-Way ANOVA = 286
• Interpretation of Results = 286
• A Look at Two-Way ANOVA Computations = 287
• Summary = 290
• Exercises = 291
• CHAPTER 13 Correlation and Regression = 293
• Linear Correlation = 294
• Classes of Correlation = 295
• Correlation and Causation = 299
• The Pearson Product-Moment Correlation Coefficient = 300
• Understanding the Pearson r Definitional Formula = 300
• Correlation, Variance, and Covariance = 301
• Testing r for Significance = 305
• The Effect of Range on Correlation = 306
• The Linear Regression Equation = 308
• The Coefficient of Determination = 313
• The Spearman Rank Order Correlation Coefficient = 314
• Other Correlation Coefficients = 318
• A Broader View of Inferential Techniques - The General Linear Model = 318
• Summary = 319
• Troubleshooting Your Computations = 321
• Exercises = 321
• CHAPTER 14 Chi Square = 326
• Nonparametric Tests = 328
• The Chi-Square Goodness-of-Fit Test = 328
• Confirming Hypotheses With Chi Square = 331
• The Chi-Square Test of Independence = 331
• An Alternative Method for Finding Expected Values = 333
• Another Chi-Square Test of Independence Example = 336
• Restrictions on Chi Square = 338
• Summary = 339
• Troubleshooting Your Computations = 340
• Exercises = 340
• CHAPTER 15 Alternatives to t and F = 344
• The Mann-Whitney U Test = 346
• The Wilcoxon Matched-Pairs Signed-Ranks Test = 353
• The Kruskal-Wallis One-Way ANOVA = 356
• Further Testing After a Significant H = 360
• Summary = 361
• Troubleshooting Your Computations = 363
• Exercises = 363
• Review of Inferential Statistics = 367
• Choosing the Correct Inferential Test = 370
• APPENDIX 1 Brief Math-Algebra Review = 372
• APPENDIX 2 Glossary of Statistical Terms = 380
• APPENDIX 3 Symbol Glossary and Glossary of Computational Formulas = 388
• APPENDIX 4 Tables for Inferential Tests = 400
• APPENDIX 5 Answers to Odd-Numbered Exercises = 413
• INDEX = 431