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This fully updated fourth edition of Research Design and Statistical Analysis provides comprehensive coverage of the design principles and statistical concepts necessary to make sense of real data.
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This fully updated fourth edition of Research Design and Statistical Analysis provides comprehensive coverage of the design principles and statistical concepts necessary to make sense of real data.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis Ltd
- 4 ed
- Seitenzahl: 814
- Erscheinungstermin: 28. Januar 2025
- Englisch
- Abmessung: 253mm x 177mm x 45mm
- Gewicht: 1532g
- ISBN-13: 9781032897288
- ISBN-10: 1032897287
- Artikelnr.: 70975621
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- gpsr@libri.de
- Verlag: Taylor & Francis Ltd
- 4 ed
- Seitenzahl: 814
- Erscheinungstermin: 28. Januar 2025
- Englisch
- Abmessung: 253mm x 177mm x 45mm
- Gewicht: 1532g
- ISBN-13: 9781032897288
- ISBN-10: 1032897287
- Artikelnr.: 70975621
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- gpsr@libri.de
Caren M. Rotello is Professor Emerita at the University of Massachusetts Amherst. She received her Ph.D. in Psychology from Stanford University. Jerome L. Myers is Professor Emeritus at the University of Massachusetts Amherst. He received his Ph.D. in Psychology from the University of Wisconsin. Arnold D. Well is Professor Emeritus at the University of Massachusetts Amherst. He received his Ph.D. in Experimental Psychology from the University of Oregon. Robert F. Lorch, Jr., is Professor Emeritus at the University of Kentucky. He received his Ph.D. in Psychology from the University of Massachusetts Amherst.
PART 1: Foundations of Research Design and Data Analysis 1. Planning the
Research 2. Describing the Data 3. Basic Concepts in Probability 4.
Developing the Fundamentals of Hypothesis Testing Using the Binomial
Distribution 5. Further Development of the Foundations of Statistical
Inference 6. The t Distribution and Its Applications 7. Integrated Analysis
I PART 2: Between-Participants Designs 8. Between-Participants Designs: One
Factor 9. Multi-Factor Between-Participants Designs 10. Contrasting Means
in Between-Subjects Designs 11. Integrated Analysis II PART 3:
Repeated-Measures Designs 12. Comparing Experimental Designs and Analyses
13. One-Factor Repeated-Measures Designs
14. Multi-Factor Repeated-Measures and Mixed Designs 15. Nested and
Counterbalanced Variables in Repeated-Measures Designs 16. Integrated
Analysis III PART 4: Correlation and Regression 17. An Introduction to
Correlation and Regression 18. More About Correlation 19. More About
Bivariate Regression 20. Introduction to Multiple Regression 21. Inference,
Assumptions, and Power in Multiple Regression 22. Additional Topics in
Multiple Regression 23. Regression with Qualitative and Quantitative
Variables 24. ANCOVA as a Special Case of Multiple Regression 25.
Integrated Analysis IV PART 5: Epilogue 26. Some Final Thoughts,
Suggestions, and Cautions APPENDICES Appendix A: Notation and Summation
Operations Appendix B: Expected Values and Their Applications Appendix C:
Statistical Tables
Answers to Selected Exercise
Research 2. Describing the Data 3. Basic Concepts in Probability 4.
Developing the Fundamentals of Hypothesis Testing Using the Binomial
Distribution 5. Further Development of the Foundations of Statistical
Inference 6. The t Distribution and Its Applications 7. Integrated Analysis
I PART 2: Between-Participants Designs 8. Between-Participants Designs: One
Factor 9. Multi-Factor Between-Participants Designs 10. Contrasting Means
in Between-Subjects Designs 11. Integrated Analysis II PART 3:
Repeated-Measures Designs 12. Comparing Experimental Designs and Analyses
13. One-Factor Repeated-Measures Designs
14. Multi-Factor Repeated-Measures and Mixed Designs 15. Nested and
Counterbalanced Variables in Repeated-Measures Designs 16. Integrated
Analysis III PART 4: Correlation and Regression 17. An Introduction to
Correlation and Regression 18. More About Correlation 19. More About
Bivariate Regression 20. Introduction to Multiple Regression 21. Inference,
Assumptions, and Power in Multiple Regression 22. Additional Topics in
Multiple Regression 23. Regression with Qualitative and Quantitative
Variables 24. ANCOVA as a Special Case of Multiple Regression 25.
Integrated Analysis IV PART 5: Epilogue 26. Some Final Thoughts,
Suggestions, and Cautions APPENDICES Appendix A: Notation and Summation
Operations Appendix B: Expected Values and Their Applications Appendix C:
Statistical Tables
Answers to Selected Exercise
PART 1: Foundations of Research Design and Data Analysis 1. Planning the
Research 2. Describing the Data 3. Basic Concepts in Probability 4.
Developing the Fundamentals of Hypothesis Testing Using the Binomial
Distribution 5. Further Development of the Foundations of Statistical
Inference 6. The t Distribution and Its Applications 7. Integrated Analysis
I PART 2: Between-Participants Designs 8. Between-Participants Designs: One
Factor 9. Multi-Factor Between-Participants Designs 10. Contrasting Means
in Between-Subjects Designs 11. Integrated Analysis II PART 3:
Repeated-Measures Designs 12. Comparing Experimental Designs and Analyses
13. One-Factor Repeated-Measures Designs
14. Multi-Factor Repeated-Measures and Mixed Designs 15. Nested and
Counterbalanced Variables in Repeated-Measures Designs 16. Integrated
Analysis III PART 4: Correlation and Regression 17. An Introduction to
Correlation and Regression 18. More About Correlation 19. More About
Bivariate Regression 20. Introduction to Multiple Regression 21. Inference,
Assumptions, and Power in Multiple Regression 22. Additional Topics in
Multiple Regression 23. Regression with Qualitative and Quantitative
Variables 24. ANCOVA as a Special Case of Multiple Regression 25.
Integrated Analysis IV PART 5: Epilogue 26. Some Final Thoughts,
Suggestions, and Cautions APPENDICES Appendix A: Notation and Summation
Operations Appendix B: Expected Values and Their Applications Appendix C:
Statistical Tables
Answers to Selected Exercise
Research 2. Describing the Data 3. Basic Concepts in Probability 4.
Developing the Fundamentals of Hypothesis Testing Using the Binomial
Distribution 5. Further Development of the Foundations of Statistical
Inference 6. The t Distribution and Its Applications 7. Integrated Analysis
I PART 2: Between-Participants Designs 8. Between-Participants Designs: One
Factor 9. Multi-Factor Between-Participants Designs 10. Contrasting Means
in Between-Subjects Designs 11. Integrated Analysis II PART 3:
Repeated-Measures Designs 12. Comparing Experimental Designs and Analyses
13. One-Factor Repeated-Measures Designs
14. Multi-Factor Repeated-Measures and Mixed Designs 15. Nested and
Counterbalanced Variables in Repeated-Measures Designs 16. Integrated
Analysis III PART 4: Correlation and Regression 17. An Introduction to
Correlation and Regression 18. More About Correlation 19. More About
Bivariate Regression 20. Introduction to Multiple Regression 21. Inference,
Assumptions, and Power in Multiple Regression 22. Additional Topics in
Multiple Regression 23. Regression with Qualitative and Quantitative
Variables 24. ANCOVA as a Special Case of Multiple Regression 25.
Integrated Analysis IV PART 5: Epilogue 26. Some Final Thoughts,
Suggestions, and Cautions APPENDICES Appendix A: Notation and Summation
Operations Appendix B: Expected Values and Their Applications Appendix C:
Statistical Tables
Answers to Selected Exercise