This textbook emphasizes contemporary research problems to better illustrate the relevance of statistical analysis in scientific research. It introduces students to statistical methods in the context of realistic problems and gives practical applications of the new skills with the use of the accompanying workbook and problem sets.
This textbook emphasizes contemporary research problems to better illustrate the relevance of statistical analysis in scientific research. It introduces students to statistical methods in the context of realistic problems and gives practical applications of the new skills with the use of the accompanying workbook and problem sets.
Harold O. Kiess is Professor Emeritus, Framingham State University, and received his Ph.D. in Experimental Psychology from the University of Illinois, Urbana-Champaign. While at Framingham, Kiess developed and taught courses in research methodology and statistical analysis, as well as the historical foundations of psychology. He has also authored three editions of Statistical Concepts for the Behavioral Sciences before joining with Bonnie A. Green as co-author for the fourth edition.
Inhaltsangabe
1. Making sense of variability: an introduction to statistics 2. Statistics in the context of scientific research 3. Looking at data: frequency distributions and graphs 4. Looking at data: measures of central tendency 5. Looking at data: measures of variability 6. The normal distribution, probability, and standard scores 7. Understanding data: using statistics for inference and estimation 8. Is there really a difference? Introduction to statistical hypothesis testing 9. The basics of experimentation and testing for a difference between means 10. One-factor between-subjects analysis of variance 11. Two-factor between-subjects analysis of variance 12. One-factor within-subjects analysis of variance 13. Correlation: understanding covariation 14. Regression analysis: predicting linear relationships 15. Nonparametric statistical tests Appendix A. Mathematics review Appendix B. Statistical symbols Appendix C. Statistical tables Appendix D. Commonly used formulas Appendix E. Answers for computational problems Appendix F. Glossary References Name index Subject index.
1. Making sense of variability: an introduction to statistics 2. Statistics in the context of scientific research 3. Looking at data: frequency distributions and graphs 4. Looking at data: measures of central tendency 5. Looking at data: measures of variability 6. The normal distribution, probability, and standard scores 7. Understanding data: using statistics for inference and estimation 8. Is there really a difference? Introduction to statistical hypothesis testing 9. The basics of experimentation and testing for a difference between means 10. One-factor between-subjects analysis of variance 11. Two-factor between-subjects analysis of variance 12. One-factor within-subjects analysis of variance 13. Correlation: understanding covariation 14. Regression analysis: predicting linear relationships 15. Nonparametric statistical tests Appendix A. Mathematics review Appendix B. Statistical symbols Appendix C. Statistical tables Appendix D. Commonly used formulas Appendix E. Answers for computational problems Appendix F. Glossary References Name index Subject index.
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