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Detection Theory: A User's Guide is an introduction to one of the most important tools for the analysis of data where choices must be made, and performance is not perfect.
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Detection Theory: A User's Guide is an introduction to one of the most important tools for the analysis of data where choices must be made, and performance is not perfect.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Jenny Stanford Publishing
- 3rd edition
- Seitenzahl: 434
- Erscheinungstermin: 28. September 2021
- Englisch
- Abmessung: 254mm x 178mm x 25mm
- Gewicht: 998g
- ISBN-13: 9780815360094
- ISBN-10: 0815360096
- Artikelnr.: 60018967
- Verlag: Jenny Stanford Publishing
- 3rd edition
- Seitenzahl: 434
- Erscheinungstermin: 28. September 2021
- Englisch
- Abmessung: 254mm x 178mm x 25mm
- Gewicht: 998g
- ISBN-13: 9780815360094
- ISBN-10: 0815360096
- Artikelnr.: 60018967
Michael J. Hautus is Head of the Psychophysics Laboratory in the School of Psychology at the University of Auckland, New Zealand. His research interests include quantitative assessment of the functioning of the auditory system, modeling auditory, visual, and flavor judgment, and modeling cognitive processes involved in judgment. Neil A. Macmillan is a retired Professor of Psychology at Brooklyn College, USA. C. Douglas Creelman, deceased, was a Professor of Psychology at the University of Toronto, Canada. Both of them were privileged to study with founders of detection theory: Creelman with Wilson Tanner and John Swets at the University of Michigan, Macmillan with David Green and Duncan Luce at the University of Pennsylvania.
PART I. Basic Detection Theory and One-Interval Designs 1. The Yes-No
Experiment: Sensitivity 2. The Yes-No Experiment: Response Bias 3. Beyond
Binary Responses: The Rating Experiment and Empirical Receiver Operating
Characteristics 4. Classification Experiments for One-Dimensional Stimulus
Sets 5. Threshold Models and Choice Theory PART II. Multidimensional
Detection Theory and Multi-Interval Discrimination Designs 6. Detection and
Discrimination of Compound Stimuli: Tools for Multidimensional Detection
Theory 7. Comparison (Two-Distribution) Designs for Discrimination 8.
Classification Designs: Attention and Interaction 9. Classification Designs
for Discrimination 10. Identification of Multidimensional Objects and
Multiple Observation Intervals PART III. Stimulus Factors 11. Adaptive
Methods for Estimating Empirical Thresholds 12. Components of Sensitivity
PART IV. Statistics 13 Statistics and Detection Theory Appendices Appendix
1. Elements of Probability and Statistics Appendix 2. Logarithms and
Exponentials Appendix 3. Flowcharts to Sensitivity and Bias Calculations
Appendix 4. Some Useful Equations Appendix 5. Tables Appendix 6. Software
for Detection Theory Appendix 7. Solutions to Selected Problems
Experiment: Sensitivity 2. The Yes-No Experiment: Response Bias 3. Beyond
Binary Responses: The Rating Experiment and Empirical Receiver Operating
Characteristics 4. Classification Experiments for One-Dimensional Stimulus
Sets 5. Threshold Models and Choice Theory PART II. Multidimensional
Detection Theory and Multi-Interval Discrimination Designs 6. Detection and
Discrimination of Compound Stimuli: Tools for Multidimensional Detection
Theory 7. Comparison (Two-Distribution) Designs for Discrimination 8.
Classification Designs: Attention and Interaction 9. Classification Designs
for Discrimination 10. Identification of Multidimensional Objects and
Multiple Observation Intervals PART III. Stimulus Factors 11. Adaptive
Methods for Estimating Empirical Thresholds 12. Components of Sensitivity
PART IV. Statistics 13 Statistics and Detection Theory Appendices Appendix
1. Elements of Probability and Statistics Appendix 2. Logarithms and
Exponentials Appendix 3. Flowcharts to Sensitivity and Bias Calculations
Appendix 4. Some Useful Equations Appendix 5. Tables Appendix 6. Software
for Detection Theory Appendix 7. Solutions to Selected Problems
PART I. Basic Detection Theory and One-Interval Designs 1. The Yes-No
Experiment: Sensitivity 2. The Yes-No Experiment: Response Bias 3. Beyond
Binary Responses: The Rating Experiment and Empirical Receiver Operating
Characteristics 4. Classification Experiments for One-Dimensional Stimulus
Sets 5. Threshold Models and Choice Theory PART II. Multidimensional
Detection Theory and Multi-Interval Discrimination Designs 6. Detection and
Discrimination of Compound Stimuli: Tools for Multidimensional Detection
Theory 7. Comparison (Two-Distribution) Designs for Discrimination 8.
Classification Designs: Attention and Interaction 9. Classification Designs
for Discrimination 10. Identification of Multidimensional Objects and
Multiple Observation Intervals PART III. Stimulus Factors 11. Adaptive
Methods for Estimating Empirical Thresholds 12. Components of Sensitivity
PART IV. Statistics 13 Statistics and Detection Theory Appendices Appendix
1. Elements of Probability and Statistics Appendix 2. Logarithms and
Exponentials Appendix 3. Flowcharts to Sensitivity and Bias Calculations
Appendix 4. Some Useful Equations Appendix 5. Tables Appendix 6. Software
for Detection Theory Appendix 7. Solutions to Selected Problems
Experiment: Sensitivity 2. The Yes-No Experiment: Response Bias 3. Beyond
Binary Responses: The Rating Experiment and Empirical Receiver Operating
Characteristics 4. Classification Experiments for One-Dimensional Stimulus
Sets 5. Threshold Models and Choice Theory PART II. Multidimensional
Detection Theory and Multi-Interval Discrimination Designs 6. Detection and
Discrimination of Compound Stimuli: Tools for Multidimensional Detection
Theory 7. Comparison (Two-Distribution) Designs for Discrimination 8.
Classification Designs: Attention and Interaction 9. Classification Designs
for Discrimination 10. Identification of Multidimensional Objects and
Multiple Observation Intervals PART III. Stimulus Factors 11. Adaptive
Methods for Estimating Empirical Thresholds 12. Components of Sensitivity
PART IV. Statistics 13 Statistics and Detection Theory Appendices Appendix
1. Elements of Probability and Statistics Appendix 2. Logarithms and
Exponentials Appendix 3. Flowcharts to Sensitivity and Bias Calculations
Appendix 4. Some Useful Equations Appendix 5. Tables Appendix 6. Software
for Detection Theory Appendix 7. Solutions to Selected Problems