Statistical concepts for the behavioral sciences:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Boston [u.a.]
Allyn and Bacon
2002
|
| Ausgabe: | 3. ed. |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XXI, 568 S. graph. Darst. |
| ISBN: | 0205332919 |
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| 245 | 1 | 0 | |a Statistical concepts for the behavioral sciences |c Harold O. Kiess |
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Datensatz im Suchindex
| _version_ | 1804138168332582912 |
|---|---|
| adam_text | Brief Contents
Chapter 1 Introduction to Statistics 1
Chapter 2 Scientific Research 14
Chapter 3 Describing Data: Frequency Distributions and Graphs 30
Chapter 4 Describing Data: Measures of Central Tendency 62
Chapter 5 Describing Data: Measures of Variability 77
Chapter 6 The Normal Distribution, Probability, and
Standard Scores 95
Chapter 7 Using Statistics for Inference and Estimation 126
Chapter 8 Introduction to Statistical Hypothesis Testing:
The z Test and the One-Sample f Test 147
Chapter 9 The Basics of Experimentation and Testing for
a Difference between Means 179
Chapter 10 One-Factor Between-Subjects Analysis of Variance 223
Chapter 11 Two-Factor Between-Subjects Designs and Analysis
of Variance 272
Chapter 12 One-Factor Within-Subjects Designs and Analysis
of Variance 333
Chapter 13 Correlation 366
Chapter 14 Regression and Prediction 407
Chapter 15 Nonparametric Statistical Tests 448
v
vi Brief Contents
Appendix A Statistical Tables 486
Appendix B Mathematics Review 502
Appendix C Glossary 507
Appendix D Statistical Symbols 514
Appendix E Answers for Computational Problems 517
Appendix F Commonly Used Formulas 545
References 554
Name Index 559
Subject Index 561
Contents
PREFACE xvii
Chapter 1 Introduction to Statistics 1
STUDYING STATISTICS: HOW TO USE THIS TEXT 3
Important Terms and Symbols 4
Testing Your Knowledge Sections 4
Review Questions 4
Mathematics Review 4
WHAT IS STATISTICS? 5
USING STATISTICS: THREE EXAMPLES 5
Description and Inference 5
Experimentation and Statistical Hypothesis Testing 7
Correlation and Regression 9
WHY ARE STATISTICS NECESSARY? 11
Summary 12
Key Terms and Symbols 12
Review Questions 12
Chapter 2 Scientific Research 14
WHAT IS SCIENCE? 15
Scientific Questions 15
Research Methods 15
Operational Definitions 17
MEASUREMENT 17
Scales of Measurement 17
Qualitative and Quantitative Data 22
Discrete and Continuous Variables 23
Summary 26
Key Terms and Symbols 27
Review Questions 27
viii Contents
Chapter 3 Describing Data: Frequency Distributions and Graphs 30
FREQUENCY DISTRIBUTIONS WITH UNGROUPED SCORES 32
Simple Frequency Distributions 32
Relative Frequency Distributions 32
Percentage Frequency Distributions 33
Obtaining Information from a Frequency Distribution 33
GROUPED FREQUENCY DISTRIBUTIONS 35
Constructing Grouped Frequency Distributions 35
PERCENTILES AND PERCENTILE RANKS 40
Finding the Percentile Rank of a Score 40
Finding a Percentile of a Distribution 42
PRESENTING FREQUENCY DISTRIBUTIONS GRAPHICALLY 46
Histograms 47
Frequency Polygons 48
Relative Frequency Histograms and Polygons 48
Obtaining Information from a Histogram or a Frequency Polygon 50
Stem-and-Leaf Displays 50
GRAPHIC PRESENTATION OF QUALITATIVE DATA 53
SHAPES OF FREQUENCY DISTRIBUTIONS 54
Symmetrical Frequency Distributions 54
Skewness 54
Modality 55
Summary 56
Key Terms and Symbols 57
Review Questions 57
Chapter 4 Describing Data: Measures of Central Tendency 62
MODE 63
MEDIAN 64
Calculating the Median with an Odd Number of Scores: No Tied Scores
near the Median 64
Calculating the Median with an Even Number of Scores: No Tied Scores
near the Median 64
Calculating the Median with the Percentile Formula 65
Characteristics of the Median 66
SAMPLE MEAN 67
Calculating the Sample Mean 67
Characteristics of the Sample Mean 68
Journal Presentation of the Sample Mean 69
POPULATION MEAN 70
COMPARING MEASURES OF CENTRAL TENDENCY 71
Descriptive Uses of Measures of Central Tendency 71
Contents
Inferential Uses of Measures of Central Tendency 74
Summary 74
Key Terms and Symbols 75
Review Questions 75
Chapter 5 Describing Data: Measures of Variability 77
RANGE MEASURES OF VARIABILITY 79
Range 79
Interquartile Range and Semi-Interquartile Range 79
MEASURES OF VARIABILITY ABOUT THE SAMPLE MEAN 80
Variance 81
Standard Deviation 82
Computational Formula for the Estimated Population Variance
and Standard Deviation 84
Finding the Variance and Standard Deviation with a Calculator 86
Review of Symbols and Formulas 86
Interpreting the Variance and the Standard Deviation 86
What Is a Large Amount of Variability? 88
Journal Presentation of Measures of Variability 88
A COMPARISON OF MEASURES OF VARIABILITY 90
THE CHOICE OF DESCRIPTIVE STATISTICS 91
Scale of Measurement 91
Shape of the Frequency Distribution 92
Further Data Analysis 92
Summary 92
Key Terms and Symbols 93
Review Questions 93
Chapter 6 The Normal Distribution, Probability,
and Standard Scores 95
NORMAL DISTRIBUTION 96
The Normal Distribution and the Behavioral Sciences 97
Properties of the Normal Distribution 97
Area under the Normal Distribution 98
STANDARD NORMAL DISTRIBUTION 100
Using a Table of the Standard Normal Distribution 102
An Example of the Use of r Scores 110
PROBABILITY 111
Properties of Discrete Probability Distributions 1 13
Theoretical and Empirical Probability 116
The Standard Normal Distribution as a Probability Distribution 116
x Contents
STANDARD SCORES 119
Summary 121
Key Terms and Symbols 122
Review Questions 122
Chapter 7 Using Statistics for Inference and Estimation 126
X AS A POINT ESTIMATOR OF n 127
Unbiased Estimator 127
Consistent Estimator 127
Accuracy of Estimation 128
ESTIMATING THE POPULATION VARIANCE
AND STANDARD DEVIATION 130
Variance 130
Standard Deviation 131
SAMPLING DISTRIBUTION OF THE MEAN: DETERMINING THE
ACCURACY OF AN ESTIMATE 131
Characteristics of the Sampling Distribution of the Mean 133
ESTIMATING THE STANDARD ERROR OF THE MEAN 137
Factors Affecting the Value of s% 138
Use of sx 138
Review of Types of Distributions 138
INTERVAL ESTIMATION OF THE POPULATION MEAN 140
Constructing a Confidence Interval 140
Summary 143
Key Terms and Symbols 144
Chapter Supplement: Review of Important Symbols and Formulas 144
Review Questions 145
Chapter 8 Introduction to Statistical Hypothesis Testing:
The z Test and the One-Sample f Test 147
STATISTICAL HYPOTHESIS TESTING 148
Parametric and Nonparametric Tests 148
Statistical Hypotheses 150
A Test Statistic: z 152
Significance Levels: Statistical Rareness 153
Using the Test Statistic and the Significance Level to Decide about
the Statistical Hypotheses 153
Summary of the Steps of Statistical Hypothesis Testing 156
THE ONE-SAMPLE t TEST 158
Sampling Distribution of f 158
Statistical Hypothesis Testing with the One-Sample / 161
REPORTING THE RESULTS OF THE ONE-SAMPLE t TEST 169
IMPORTANT CONSIDERATIONS IN STATISTICAL
HYPOTHESIS TESTING 171
Contents xi
Why We Don t Accept the Null Hypothesis 171
Type I and Type II Errors in Statistical Tests 172
Statistical and Scientific Significance 173
USING THE t STATISTIC TO CONSTRUCT CONFIDENCE INTERVALS
FOR THE POPULATION MEAN 174
Summary 175
Key Terms and Symbols 176
Review Questions 177
Chapter 9 The Basics of Experimentation and Testing
for a Difference between Means 179
A REVIEW OF THE RESEARCH PROCESS 180
Asking a Scientific Question and Formulating the Research Hypothesis 181
Selecting a Research Design 181
Selecting Participants 181
Creating Equivalent Groups 182
Manipulating the Independent Variable 182
Controlling Extraneous Variables 183
Measuring the Dependent Variable 184
DID THE TREATMENT HAVE AN EFFECT? THE NEED
FOR STATISTICAL TESTING 186
The Implications of Sampling Error for an Experiment 186
An Overview of Statistical Hypothesis Testing for the Difference
between Two Means 186
THE t TEST FOR TWO INDEPENDENT GROUPS 187
Sampling Distribution of Differences between Means 188
Statistical Testing with tind 191
POWER AND t-nd 202
MEASURING THE STRENGTH OF A TREATMENT EFFECT 203
USING THE t STATISTIC TO CONSTRUCT CONFIDENCE INTERVALS
FOR THE DIFFERENCE BETWEEN TWO INDEPENDENT
POPULATION MEANS 205
WHAT DOES A t TEST ACTUALLY TEST? 206
STATISTICAL AND SCIENTIFIC SIGNIFICANCE REVISITED 207
THE CONTROVERSY OVER STATISTICAL HYPOTHESIS TESTING 207
REPORTING THE RESULTS OF A t TEST 209
WITHIN-SUBJECTS DESIGNS AND THE f TEST FOR RELATED SCORES 211
The t Test for Related Scores 211
Constructing Confidence Intervals for the Difference between Two
Related Population Means 214
Summary 216
Key Terms and Symbols 217
Review Questions 217
xii Contents
Chapter 10 One-Factor Between-Subjects Analysis of Variance 223
AN EXAMPLE ONE-FACTOR MULTILEVEL DESIGN 224
BETWEEN-GROUPS AND WITHIN-GROUPS VARIATION 225
OBTAINING THE F STATISTIC 227
Partitioning a Score 228
Obtaining Mean Squares from Partitioned Scores 231
Computing the F Statistic 236
STATISTICAL HYPOTHESIS TESTING WITH F 239
Factors Affecting the Value of MSA and MSError 239
Statistical Decision Making from the F Statistic 241
Assumptions of One-Factor Between-Subjects Analysis of Variance 245
INTERPRETING A STATISTICALLY SIGNIFICANT F IN A
MULTILEVEL DESIGN 247
Multiple Comparison Tests 247
The Tukey HSD Test for Post Hoc Comparisons 248
MEASURING THE STRENGTH OF A TREATMENT EFFECT 250
Calculating Eta Squared for the Analysis of Variance 250
THE RELATIONSHIP BETWEEN find AND F 251
REPORTING THE RESULTS OF THE ANALYSIS OF VARIANCE 260
Summary 263
Key Terms and Symbols 264
Chapter Supplement: Calculating a One-Factor Between-Subjects Analysis
of Variance with Computational Formulas 264
Review Questions 267
Chapter 11 Two-Factor Between-Subjects Designs
and Analysis of Variance 272
AN EXAMPLE 2x2 BETWEEN-SUBJECTS DESIGN 274
INFORMATION OBTAINED FROM A FACTORIAL DESIGN 275
Cell Means 276
Main Effect Means 276
Interaction of the Independent Variables 278
ANALYSIS OF VARIANCE OF A TWO-FACTOR
BETWEEN-SUBJECTS DESIGN 279
Partitioning a Score 280
Obtaining Mean Squares from Partitioned Scores 282
Computing the F Statistics 288
STATISTICAL HYPOTHESIS TESTING WITH THE TWO-FACTOR
BETWEEN-SUBJECTS ANALYSIS OF VARIANCE 291
Factors Affecting the Value of Mean Squares in a Factorial Analysis
of Variance 291
Statistical Decision Making from the F Statistics 292
Assumptions of Factorial Between-Subjects Analysis of Variance 295
Contents xiii
INTERPRETING A 2 X 2 FACTORIAL ANALYSIS OF VARIANCE 296
The Simple Effect of an Independent Variable 296
Putting It All Together: Interpreting the Analysis of Variance on
the Example Experiment 302
Measuring the Strength of a Treatment Effect in a Factorial Analysis
of Variance 306
REPORTING THE RESULTS OF A FACTORIAL ANALYSIS
OF VARIANCE 317
Summary 321
Key Terms and Symbols 322
Chapter Supplement: Calculating a Two-Factor Between-Subjects Analysis
of Variance with Computational Formulas 322
Review Questions 326
Chapter 12 One-Factor Within-Subjects Designs and Analysis
of Variance 333
AN EXAMPLE ONE-FACTOR WITHIN-SUBJECTS EXPERIMENT 334
ONE-FACTOR WITHIN-SUBJECTS ANALYSIS OF VARIANCE 337
Partitioning a Score and Obtaining Sums of Squares 337
Finding Degrees of Freedom 339
Finding Mean Squares and F 341
STATISTICAL HYPOTHESIS TESTING WITH Fobs 344
Measuring the Strength of a Treatment Effect 347
Assumptions of a Within-Subjects Analysis of Variance 348
REPORTING THE RESULTS OF THE ANALYSIS OF VARIANCE 354
CHOICE OF RESEARCH DESIGN: BETWEEN SUBJECTS
OR WITHIN SUBJECTS 355
Number of Participants Needed 355
Effectiveness of the Independent Variable 355
Multiple Treatment Effects 356
Summary 358
Ke y Te rm s a n d S y m bo I s 35 9
Chapter Supplement: Calculating a One-Factor Within-Subjects Analysis
of Variance with Computational Formulas 359
Review Questions 362
Chapter 13 Correlation 366
SCATTERPLOTS 368
Positive Relationships 368
Negative Relationships 370
THE PEARSON CORRELATION COEFFICIENT 373
Obtaining a Measure of Covariation: Cross Products 374
r. Comparing the CPXY with a Measure of the Total Variation in Scores 377
xiv Contents
ALTERNATIVE FORMULAS FOR THE PEARSON CORRELATION 380
Standard Scores Formula for r 380
Computational Formula for r 382
SUMMARY OF FORMULAS FOR r 382
CHARACTERISTICS OF r 385
Direction of Relationship 386
Degree of Relationship 386
Restriction of Range and the Value of r 387
Coefficient of Determination 388
Correlation and Causality 388
TESTING THE STATISTICAL SIGNIFICANCE OF THE PEARSON r 390
The Population Correlation, p 390
Testing for a Nonzero Correlation in the Population 390
REPORTING THE RESULTS OF A CORRELATIONAL STUDY 395
THE SPEARMAN RANK-ORDER CORRELATION COEFFICIENT 396
An Example of the Use of rs 396
Statistical Significance of the Spearman Rank-Order Correlation 397
Characteristics of rs 398
Summary 399
Key Terms and Symbols 400
Review Questions 400
Chapter 14 Regression and Prediction 407
LINEAR RELATIONS 408
Definition of a Linear Relation 408
Slope of a Line 410
The y-Intercept of a Line 411
Example Linear Relations and Their Equations 412
FINDING A LINEAR REGRESSION LINE 415
An Example Problem 415
A More Realistic Example Problem 417
The Least-Squares Criterion 419
The Slope and y-Intercept of a Least-Squares Regression Line
for Predicting Y from X 421
Fitting a Least-Squares Regression Line to Scores 425
ERROR IN PREDICTION 425
Residuals: A Measure of the Error in Prediction 425
The Standard Error of Estimate 426
Computational Formula for Calculating sY.x ATI
Calculating sYX from r 429
Information Provided by the Standard Error of Estimate 429
Contents xv
PREDICTING X FROM Y 431
USING A LINEAR REGRESSION LINE 432
MULTIPLE REGRESSION 440
Summary 443
Key Terms and Symbols 444
Review Questions 444
Chapter 15 Non para metric Statistical Tests 448
ANALYSIS OF FREQUENCY DATA: THE CHI-SQUARE TEST 449
The Chi-Square Test of Independence 450
THE x2 TEST FOR GOODNESS OF FIT 458
REPORTING THE RESULTS OF THE CHI-SQUARE TEST 460
MANN-WHITNEY U TEST 462
Statistical Hypothesis Testing with the Mann-Whitney U 463
Assumptions of the Mann-Whitney U Test 467
Computational Formulas for U 467
REPORTING THE RESULTS OF THE MANN-WHITNEY U TEST 471
THE WILCOXON SIGNED-RANKS TEST 473
Statistical Hypothesis Testing with the Wilcoxon Signed-Ranks Test 474
REPORTING THE RESULTS OF THE WILCOXON
SIGNED-RANKS TEST 478
USING NONPARAMETRIC TESTS 478
Summary 480
Key Terms and Symbols 481
Review Questions 481
Appendix A Statistical Tables 486
Appendix B Mathematics Review 502
Appendix C Glossary 507
Appendix D Statistical Symbols 514
Appendix E Answers for Computational Problems 517
Appendix F Commonly Used Formulas 545
REFERENCES 554
NAME INDEX 559
SUBJECT INDEX 561
|
| adam_txt |
Brief Contents
Chapter 1 Introduction to Statistics 1
Chapter 2 Scientific Research 14
Chapter 3 Describing Data: Frequency Distributions and Graphs 30
Chapter 4 Describing Data: Measures of Central Tendency 62
Chapter 5 Describing Data: Measures of Variability 77
Chapter 6 The Normal Distribution, Probability, and
Standard Scores 95
Chapter 7 Using Statistics for Inference and Estimation 126
Chapter 8 Introduction to Statistical Hypothesis Testing:
The z Test and the One-Sample f Test 147
Chapter 9 The Basics of Experimentation and Testing for
a Difference between Means 179
Chapter 10 One-Factor Between-Subjects Analysis of Variance 223
Chapter 11 Two-Factor Between-Subjects Designs and Analysis
of Variance 272
Chapter 12 One-Factor Within-Subjects Designs and Analysis
of Variance 333
Chapter 13 Correlation 366
Chapter 14 Regression and Prediction 407
Chapter 15 Nonparametric Statistical Tests 448
v
vi Brief Contents
Appendix A Statistical Tables 486
Appendix B Mathematics Review 502
Appendix C Glossary 507
Appendix D Statistical Symbols 514
Appendix E Answers for Computational Problems 517
Appendix F Commonly Used Formulas 545
References 554
Name Index 559
Subject Index 561
Contents
PREFACE xvii
Chapter 1 Introduction to Statistics 1
STUDYING STATISTICS: HOW TO USE THIS TEXT 3
Important Terms and Symbols 4
Testing Your Knowledge Sections 4
Review Questions 4
Mathematics Review 4
WHAT IS STATISTICS? 5
USING STATISTICS: THREE EXAMPLES 5
Description and Inference 5
Experimentation and Statistical Hypothesis Testing 7
Correlation and Regression 9
WHY ARE STATISTICS NECESSARY? 11
Summary 12
Key Terms and Symbols 12
Review Questions 12
Chapter 2 Scientific Research 14
WHAT IS SCIENCE? 15
Scientific Questions 15
Research Methods 15
Operational Definitions 17
MEASUREMENT 17
Scales of Measurement 17
Qualitative and Quantitative Data 22
Discrete and Continuous Variables 23
Summary 26
Key Terms and Symbols 27
Review Questions 27
viii Contents
Chapter 3 Describing Data: Frequency Distributions and Graphs 30
FREQUENCY DISTRIBUTIONS WITH UNGROUPED SCORES 32
Simple Frequency Distributions 32
Relative Frequency Distributions 32
Percentage Frequency Distributions 33
Obtaining Information from a Frequency Distribution 33
GROUPED FREQUENCY DISTRIBUTIONS 35
Constructing Grouped Frequency Distributions 35
PERCENTILES AND PERCENTILE RANKS 40
Finding the Percentile Rank of a Score 40
Finding a Percentile of a Distribution 42
PRESENTING FREQUENCY DISTRIBUTIONS GRAPHICALLY 46
Histograms 47
Frequency Polygons 48
Relative Frequency Histograms and Polygons 48
Obtaining Information from a Histogram or a Frequency Polygon 50
Stem-and-Leaf Displays 50
GRAPHIC PRESENTATION OF QUALITATIVE DATA 53
SHAPES OF FREQUENCY DISTRIBUTIONS 54
Symmetrical Frequency Distributions 54
Skewness 54
Modality 55
Summary 56
Key Terms and Symbols 57
Review Questions 57
Chapter 4 Describing Data: Measures of Central Tendency 62
MODE 63
MEDIAN 64
Calculating the Median with an Odd Number of Scores: No Tied Scores
near the Median 64
Calculating the Median with an Even Number of Scores: No Tied Scores
near the Median 64
Calculating the Median with the Percentile Formula 65
Characteristics of the Median 66
SAMPLE MEAN 67
Calculating the Sample Mean 67
Characteristics of the Sample Mean 68
Journal Presentation of the Sample Mean 69
POPULATION MEAN 70
COMPARING MEASURES OF CENTRAL TENDENCY 71
Descriptive Uses of Measures of Central Tendency 71
Contents
Inferential Uses of Measures of Central Tendency 74
Summary 74
Key Terms and Symbols 75
Review Questions 75
Chapter 5 Describing Data: Measures of Variability 77
RANGE MEASURES OF VARIABILITY 79
Range 79
Interquartile Range and Semi-Interquartile Range 79
MEASURES OF VARIABILITY ABOUT THE SAMPLE MEAN 80
Variance 81
Standard Deviation 82
Computational Formula for the Estimated Population Variance
and Standard Deviation 84
Finding the Variance and Standard Deviation with a Calculator 86
Review of Symbols and Formulas 86
Interpreting the Variance and the Standard Deviation 86
What Is a Large Amount of Variability? 88
Journal Presentation of Measures of Variability 88
A COMPARISON OF MEASURES OF VARIABILITY 90
THE CHOICE OF DESCRIPTIVE STATISTICS 91
Scale of Measurement 91
Shape of the Frequency Distribution 92
Further Data Analysis 92
Summary 92
Key Terms and Symbols 93
Review Questions 93
Chapter 6 The Normal Distribution, Probability,
and Standard Scores 95
NORMAL DISTRIBUTION 96
The Normal Distribution and the Behavioral Sciences 97
Properties of the Normal Distribution 97
Area under the Normal Distribution 98
STANDARD NORMAL DISTRIBUTION 100
Using a Table of the Standard Normal Distribution 102
An Example of the Use of r Scores 110
PROBABILITY 111
Properties of Discrete Probability Distributions 1 13
Theoretical and Empirical Probability 116
The Standard Normal Distribution as a Probability Distribution 116
x Contents
STANDARD SCORES 119
Summary 121
Key Terms and Symbols 122
Review Questions 122
Chapter 7 Using Statistics for Inference and Estimation 126
X AS A POINT ESTIMATOR OF n 127
Unbiased Estimator 127
Consistent Estimator 127
Accuracy of Estimation 128
ESTIMATING THE POPULATION VARIANCE
AND STANDARD DEVIATION 130
Variance 130
Standard Deviation 131
SAMPLING DISTRIBUTION OF THE MEAN: DETERMINING THE
ACCURACY OF AN ESTIMATE 131
Characteristics of the Sampling Distribution of the Mean 133
ESTIMATING THE STANDARD ERROR OF THE MEAN 137
Factors Affecting the Value of s% 138
Use of sx 138
Review of Types of Distributions 138
INTERVAL ESTIMATION OF THE POPULATION MEAN 140
Constructing a Confidence Interval 140
Summary 143
Key Terms and Symbols 144
Chapter Supplement: Review of Important Symbols and Formulas 144
Review Questions 145
Chapter 8 Introduction to Statistical Hypothesis Testing:
The z Test and the One-Sample f Test 147
STATISTICAL HYPOTHESIS TESTING 148
Parametric and Nonparametric Tests 148
Statistical Hypotheses 150
A Test Statistic: z 152
Significance Levels: Statistical Rareness 153
Using the Test Statistic and the Significance Level to Decide about
the Statistical Hypotheses 153
Summary of the Steps of Statistical Hypothesis Testing 156
THE ONE-SAMPLE t TEST 158
Sampling Distribution of f 158
Statistical Hypothesis Testing with the One-Sample / 161
REPORTING THE RESULTS OF THE ONE-SAMPLE t TEST 169
IMPORTANT CONSIDERATIONS IN STATISTICAL
HYPOTHESIS TESTING 171
Contents xi
Why We Don't Accept the Null Hypothesis 171
Type I and Type II Errors in Statistical Tests 172
Statistical and Scientific Significance 173
USING THE t STATISTIC TO CONSTRUCT CONFIDENCE INTERVALS
FOR THE POPULATION MEAN 174
Summary 175
Key Terms and Symbols 176
Review Questions 177
Chapter 9 The Basics of Experimentation and Testing
for a Difference between Means 179
A REVIEW OF THE RESEARCH PROCESS 180
Asking a Scientific Question and Formulating the Research Hypothesis 181
Selecting a Research Design 181
Selecting Participants 181
Creating Equivalent Groups 182
Manipulating the Independent Variable 182
Controlling Extraneous Variables 183
Measuring the Dependent Variable 184
DID THE TREATMENT HAVE AN EFFECT? THE NEED
FOR STATISTICAL TESTING 186
The Implications of Sampling Error for an Experiment 186
An Overview of Statistical Hypothesis Testing for the Difference
between Two Means 186
THE t TEST FOR TWO INDEPENDENT GROUPS 187
Sampling Distribution of Differences between Means 188
Statistical Testing with tind 191
POWER AND t-nd 202
MEASURING THE STRENGTH OF A TREATMENT EFFECT 203
USING THE t STATISTIC TO CONSTRUCT CONFIDENCE INTERVALS
FOR THE DIFFERENCE BETWEEN TWO INDEPENDENT
POPULATION MEANS 205
WHAT DOES A t TEST ACTUALLY TEST? 206
STATISTICAL AND SCIENTIFIC SIGNIFICANCE REVISITED 207
THE CONTROVERSY OVER STATISTICAL HYPOTHESIS TESTING 207
REPORTING THE RESULTS OF A t TEST 209
WITHIN-SUBJECTS DESIGNS AND THE f TEST FOR RELATED SCORES 211
The t Test for Related Scores 211
Constructing Confidence Intervals for the Difference between Two
Related Population Means 214
Summary 216
Key Terms and Symbols 217
Review Questions 217
xii Contents
Chapter 10 One-Factor Between-Subjects Analysis of Variance 223
AN EXAMPLE ONE-FACTOR MULTILEVEL DESIGN 224
BETWEEN-GROUPS AND WITHIN-GROUPS VARIATION 225
OBTAINING THE F STATISTIC 227
Partitioning a Score 228
Obtaining Mean Squares from Partitioned Scores 231
Computing the F Statistic 236
STATISTICAL HYPOTHESIS TESTING WITH F 239
Factors Affecting the Value of MSA and MSError 239
Statistical Decision Making from the F Statistic 241
Assumptions of One-Factor Between-Subjects Analysis of Variance 245
INTERPRETING A STATISTICALLY SIGNIFICANT F IN A
MULTILEVEL DESIGN 247
Multiple Comparison Tests 247
The Tukey HSD Test for Post Hoc Comparisons 248
MEASURING THE STRENGTH OF A TREATMENT EFFECT 250
Calculating Eta Squared for the Analysis of Variance 250
THE RELATIONSHIP BETWEEN find AND F 251
REPORTING THE RESULTS OF THE ANALYSIS OF VARIANCE 260
Summary 263
Key Terms and Symbols 264
Chapter Supplement: Calculating a One-Factor Between-Subjects Analysis
of Variance with Computational Formulas 264
Review Questions 267
Chapter 11 Two-Factor Between-Subjects Designs
and Analysis of Variance 272
AN EXAMPLE 2x2 BETWEEN-SUBJECTS DESIGN 274
INFORMATION OBTAINED FROM A FACTORIAL DESIGN 275
Cell Means 276
Main Effect Means 276
Interaction of the Independent Variables 278
ANALYSIS OF VARIANCE OF A TWO-FACTOR
BETWEEN-SUBJECTS DESIGN 279
Partitioning a Score 280
Obtaining Mean Squares from Partitioned Scores 282
Computing the F Statistics 288
STATISTICAL HYPOTHESIS TESTING WITH THE TWO-FACTOR
BETWEEN-SUBJECTS ANALYSIS OF VARIANCE 291
Factors Affecting the Value of Mean Squares in a Factorial Analysis
of Variance 291
Statistical Decision Making from the F Statistics 292
Assumptions of Factorial Between-Subjects Analysis of Variance 295
Contents xiii
INTERPRETING A 2 X 2 FACTORIAL ANALYSIS OF VARIANCE 296
The Simple Effect of an Independent Variable 296
Putting It All Together: Interpreting the Analysis of Variance on
the Example Experiment 302
Measuring the Strength of a Treatment Effect in a Factorial Analysis
of Variance 306
REPORTING THE RESULTS OF A FACTORIAL ANALYSIS
OF VARIANCE 317
Summary 321
Key Terms and Symbols 322
Chapter Supplement: Calculating a Two-Factor Between-Subjects Analysis
of Variance with Computational Formulas 322
Review Questions 326
Chapter 12 One-Factor Within-Subjects Designs and Analysis
of Variance 333
AN EXAMPLE ONE-FACTOR WITHIN-SUBJECTS EXPERIMENT 334
ONE-FACTOR WITHIN-SUBJECTS ANALYSIS OF VARIANCE 337
Partitioning a Score and Obtaining Sums of Squares 337
Finding Degrees of Freedom 339
Finding Mean Squares and F 341
STATISTICAL HYPOTHESIS TESTING WITH Fobs 344
Measuring the Strength of a Treatment Effect 347
Assumptions of a Within-Subjects Analysis of Variance 348
REPORTING THE RESULTS OF THE ANALYSIS OF VARIANCE 354
CHOICE OF RESEARCH DESIGN: BETWEEN SUBJECTS
OR WITHIN SUBJECTS 355
Number of Participants Needed 355
Effectiveness of the Independent Variable 355
Multiple Treatment Effects 356
Summary 358
Ke y Te rm s a n d S y m bo I s 35 9
Chapter Supplement: Calculating a One-Factor Within-Subjects Analysis
of Variance with Computational Formulas 359
Review Questions 362
Chapter 13 Correlation 366
SCATTERPLOTS 368
Positive Relationships 368
Negative Relationships 370
THE PEARSON CORRELATION COEFFICIENT 373
Obtaining a Measure of Covariation: Cross Products 374
r. Comparing the CPXY with a Measure of the Total Variation in Scores 377
xiv Contents
ALTERNATIVE FORMULAS FOR THE PEARSON CORRELATION 380
Standard Scores Formula for r 380
Computational Formula for r 382
SUMMARY OF FORMULAS FOR r 382
CHARACTERISTICS OF r 385
Direction of Relationship 386
Degree of Relationship 386
Restriction of Range and the Value of r 387
Coefficient of Determination 388
Correlation and Causality 388
TESTING THE STATISTICAL SIGNIFICANCE OF THE PEARSON r 390
The Population Correlation, p 390
Testing for a Nonzero Correlation in the Population 390
REPORTING THE RESULTS OF A CORRELATIONAL STUDY 395
THE SPEARMAN RANK-ORDER CORRELATION COEFFICIENT 396
An Example of the Use of rs 396
Statistical Significance of the Spearman Rank-Order Correlation 397
Characteristics of rs 398
Summary 399
Key Terms and Symbols 400
Review Questions 400
Chapter 14 Regression and Prediction 407
LINEAR RELATIONS 408
Definition of a Linear Relation 408
Slope of a Line 410
The y-Intercept of a Line 411
Example Linear Relations and Their Equations 412
FINDING A LINEAR REGRESSION LINE 415
An Example Problem 415
A More Realistic Example Problem 417
The Least-Squares Criterion 419
The Slope and y-Intercept of a Least-Squares Regression Line
for Predicting Y from X 421
Fitting a Least-Squares Regression Line to Scores 425
ERROR IN PREDICTION 425
Residuals: A Measure of the Error in Prediction 425
The Standard Error of Estimate 426
Computational Formula for Calculating sY.x ATI
Calculating sYX from r 429
Information Provided by the Standard Error of Estimate 429
Contents xv
PREDICTING X FROM Y 431
USING A LINEAR REGRESSION LINE 432
MULTIPLE REGRESSION 440
Summary 443
Key Terms and Symbols 444
Review Questions 444
Chapter 15 Non para metric Statistical Tests 448
ANALYSIS OF FREQUENCY DATA: THE CHI-SQUARE TEST 449
The Chi-Square Test of Independence 450
THE x2 TEST FOR GOODNESS OF FIT 458
REPORTING THE RESULTS OF THE CHI-SQUARE TEST 460
MANN-WHITNEY U TEST 462
Statistical Hypothesis Testing with the Mann-Whitney U 463
Assumptions of the Mann-Whitney U Test 467
Computational Formulas for U 467
REPORTING THE RESULTS OF THE MANN-WHITNEY U TEST 471
THE WILCOXON SIGNED-RANKS TEST 473
Statistical Hypothesis Testing with the Wilcoxon Signed-Ranks Test 474
REPORTING THE RESULTS OF THE WILCOXON
SIGNED-RANKS TEST 478
USING NONPARAMETRIC TESTS 478
Summary 480
Key Terms and Symbols 481
Review Questions 481
Appendix A Statistical Tables 486
Appendix B Mathematics Review 502
Appendix C Glossary 507
Appendix D Statistical Symbols 514
Appendix E Answers for Computational Problems 517
Appendix F Commonly Used Formulas 545
REFERENCES 554
NAME INDEX 559
SUBJECT INDEX 561 |
| any_adam_object | 1 |
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| author | Kiess, Harold O. |
| author_facet | Kiess, Harold O. |
| author_role | aut |
| author_sort | Kiess, Harold O. |
| author_variant | h o k ho hok |
| building | Verbundindex |
| bvnumber | BV023525382 |
| callnumber-first | H - Social Science |
| callnumber-label | HA29 |
| callnumber-raw | HA29.K4857 2002 |
| callnumber-search | HA29.K4857 2002 |
| callnumber-sort | HA 229 K4857 42002 |
| callnumber-subject | HA - Statistics |
| classification_rvk | MR 2100 SK 830 |
| ctrlnum | (OCoLC)915848076 (DE-599)BVBBV023525382 |
| dewey-full | 519.521 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.5 21 |
| dewey-search | 519.5 21 |
| dewey-sort | 3519.5 221 |
| dewey-tens | 510 - Mathematics |
| discipline | Soziologie Mathematik |
| discipline_str_mv | Soziologie Mathematik |
| edition | 3. ed. |
| format | Book |
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| spelling | Kiess, Harold O. Verfasser aut Statistical concepts for the behavioral sciences Harold O. Kiess 3. ed. Boston [u.a.] Allyn and Bacon 2002 XXI, 568 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Sozialwissenschaften Statistik Social sciences -- Statistical methods Statistics Statistik (DE-588)4056995-0 gnd rswk-swf Forschungsmethode (DE-588)4155046-8 gnd rswk-swf Psychologie (DE-588)4047704-6 gnd rswk-swf Sozialwissenschaften (DE-588)4055916-6 gnd rswk-swf (DE-588)4151278-9 Einführung gnd-content (DE-588)4123623-3 Lehrbuch gnd-content Sozialwissenschaften (DE-588)4055916-6 s Statistik (DE-588)4056995-0 s DE-604 Psychologie (DE-588)4047704-6 s Forschungsmethode (DE-588)4155046-8 s 1\p DE-604 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016845624&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Kiess, Harold O. Statistical concepts for the behavioral sciences Sozialwissenschaften Statistik Social sciences -- Statistical methods Statistics Statistik (DE-588)4056995-0 gnd Forschungsmethode (DE-588)4155046-8 gnd Psychologie (DE-588)4047704-6 gnd Sozialwissenschaften (DE-588)4055916-6 gnd |
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| title | Statistical concepts for the behavioral sciences |
| title_auth | Statistical concepts for the behavioral sciences |
| title_exact_search | Statistical concepts for the behavioral sciences |
| title_exact_search_txtP | Statistical concepts for the behavioral sciences |
| title_full | Statistical concepts for the behavioral sciences Harold O. Kiess |
| title_fullStr | Statistical concepts for the behavioral sciences Harold O. Kiess |
| title_full_unstemmed | Statistical concepts for the behavioral sciences Harold O. Kiess |
| title_short | Statistical concepts for the behavioral sciences |
| title_sort | statistical concepts for the behavioral sciences |
| topic | Sozialwissenschaften Statistik Social sciences -- Statistical methods Statistics Statistik (DE-588)4056995-0 gnd Forschungsmethode (DE-588)4155046-8 gnd Psychologie (DE-588)4047704-6 gnd Sozialwissenschaften (DE-588)4055916-6 gnd |
| topic_facet | Sozialwissenschaften Statistik Social sciences -- Statistical methods Statistics Forschungsmethode Psychologie Einführung Lehrbuch |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016845624&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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