8th Edition
Making Sense of Statistics A Conceptual Overview
Making Sense of Statistics, Eighth Edition, is the ideal introduction to the concepts of descriptive and inferential statistics for students undertaking their first research project. It presents each statistical concept in a series of short steps, then uses worked examples and exercises to enable students to apply their own learning.
It focuses on presenting the “why,” as well as the “how” of statistical concepts, rather than computations and formulas. As such, it is suitable for students from all disciplines regardless of mathematical background. Only statistical techniques that are almost universally included in introductory statistics courses, and widely reported in journals, have been included.
This conceptual book is useful for all study levels, from undergraduate to doctoral level across disciplines. Once students understand and feel comfortable with the statistics presented in this book, they should find it easy to master additional statistical concepts.
New to the Eighth Edition
- Reorganization of chapters to allow better progress in conceptual understanding
- Additional discussions on program evaluation, displays of outcomes, and examples
- Chapter objectives at the beginning of each chapter are listed with clear learning objectives for the reader
- Expanded appendices include a reference to common computational formulas and examples
- A glossary of key terms has been updated to function as a useful vocabulary list for use in a first course in statistics
- Updated online resources, including a basic math review and answers, PowerPoint slides, and a test bank of questions
Introduction: What is Research?; Part A: The Research Context 1. The Empirical Approach to Knowledge 2. Types of Empirical Research 3. Scales of Measurement 4. Descriptive, Correlational, and Inferential Statistics; Part B: Sampling 5. Introduction to Sampling 6. Variations on Random Sampling 7. Sample Size 8. Standard Error of Mean and Central Limit Theorem; Part C: Descriptive Statistics 9. Frequencies, Percentages, and Proportions 10. Shapes of Distributions 11. The Mean: An Average 12. Mean, Median, and Mode 13. Range and Interquartile Range 14. Standard Deviation 15. Z Score; Part D: Correlational Statistics 16. Correlation 17. Pearson r 18. Scattergram 19. Coefficient of Determination 20. Multiple Correlation; Part E: Inferential Statistics 21. Introduction to Null Hypothesis 22. Decisions About the Null Hypothesis 23. Limits of Significance Testing and Practical Implications; Part F: Means Comparison 24. Introduction to the t Test 25. Independent Samples t Test 26. Dependent Samples t Test 27. One Sample t Test 28. Reporting the Results of t Tests: Display of Outcomes 29. One-Way ANOVA 30. Two-Way ANOVA; Part G: Predictive Significance 31. Chi-Square 32. Effect Size 33. Simple and Multiple Linear Regressions; Appendix A. Computations Appendix B. Notes on Interpreting Pearson r and Linear Regression Appendix C. Table of Random Numbers
Biography
Deborah Mikyo Oh has been Professor in Research Methods and Statistics at California State University, Los Angeles, USA, since 1998. She earned her PhD from Columbia University, New York, USA, and teaches statistics to a diverse student population at undergraduate, graduate, and doctoral levels.
