简介
在线阅读本书
A comprehensive and user–friendly introduction to statistics–now revised and updated
Introductory Statistics for the Behavioral Sciences has had a long and successful history and is a popular and well–respected statistics text. Now in its sixth edition, the text has been thoroughly revised to present all the topics students in the behavioral sciences need in a uniquely accessible format that aids in the comprehension and implementation of the statistical analyses most commonly used in the behavioral sciences.
Using a continuous narrative that explains statistics and tracks a common data set throughout, the authors have developed an innovative approach that makes the material unintimidating and memorable, providing a framework that connects all of the topics in the text and allows for easy comparison of different statistical analyses.
New features in this Sixth Edition include:
? Different aspects of a common data set are used to illustrate the various statistical methods throughout the text, with an emphasis on drawing connections between seemingly disparate statistical procedures and formulas
? Computer exercises based on the same large data set and relevant to that chapter′s content. The data set can be analyzed by any available statistical software
? New "Bridge to SPSS" sections at the end of each chapter explain, for those using this very popular statistical package, how to perform that chapter′s statistical procedures by computer, and how to translate the output from SPSS
? New chapters on multiple comparisons and repeated–measures ANOVA
目录
Preface p. xv
Acknowledgments p. xix
Glossary of Symbols p. xxi
Descriptive Statistics p. 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
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
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
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
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
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
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
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
Basic Inferential Statistics p. 123
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
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
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
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
Equivalence of the Various Formulas for r p. 236
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
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
Analysis of Variance Methods p. 287
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
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
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
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
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
Nonparametric Statistics p. 387
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
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
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
Acknowledgments p. xix
Glossary of Symbols p. xxi
Descriptive Statistics p. 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
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
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
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
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
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
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
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
Basic Inferential Statistics p. 123
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
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
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
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
Equivalence of the Various Formulas for r p. 236
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
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
Analysis of Variance Methods p. 287
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
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
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
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
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
Nonparametric Statistics p. 387
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
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
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
- 名称
- 类型
- 大小
光盘服务联系方式: 020-38250260 客服QQ：4006604884
云图客服：
用户发送的提问，这种方式就需要有位在线客服来回答用户的问题，这种 就属于对话式的,问题是这种提问是否需要用户登录才能提问
Video Player
×
Audio Player
×
pdf Player
×
亲爱的云图用户，
光盘内的文件都可以直接点击浏览哦
无需下载，在线查阅资料！
