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List of contents
Introduction to the Seventh Edition
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 the Mean and Central Limits 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
Part E Inferential Statistics
19. Introduction to Null Hypothesis
20. Decisions About the Null Hypothesis
Part F Means Comparison
21. Introduction to the t Test
22. Independent Sample t Test
23. Paired Sample t Test
24. One Sample t Test
25. Reports of the Results of t Tests
26. One-Way ANOVA
27. Two-Way ANOVA
Part G Predictive Significance
28. Chi-Square
29. Limits of Significance Testing
30. Effect Size
31. Coefficient of Determination
32. Multiple Correlations
33. Simple and Multiple Regressions
Appendix A. Computations
Appendix B. Notes on Interpreting Pearson r and Linear Regression
Appendix C. Table of Random Numbers
Appendix D. More About the Null Hypothesis
Comprehensive Review Questions
Glossary
About the author
Dr Deborah M. Oh is professor in Research Methods and Statistics at California State University, Los Angeles since 1998. She earned her PhD from Columbia University, New York and teaches statistics to a diverse student population in both undergraduate and graduate levels.
Summary
Making Sense of Statistics 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 formulae, so 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. Once students understand and feel comfortable with the statistics that meet these criteria, they should find it easy to master additional statistical concepts.
New to the Seventh Edition
Retaining the key features and organization that have made this book an indispensable text for teaching and learning the basic concepts of statistical analysis, this new edition features:
- discussion of the use of observation in quantitative and qualitative research
- the inclusion of introductions to the book, and each Part.
- section objectives listed at the beginning of each section to guide the reader.
- new material on key topics such as z-scores, probability, Central Limit Theorem, Standard Deviation and simple and multiple regression
- Expanded discussion on t test with separate sections for independent and dependent samples t tests, as well as one-sample t test
- progressive analysis of bivariate vs multivariate statistics (starts with the basic concepts and moves to more complex analysis as the student progresses)
- updated and extended pedagogical material such as Chapter Objectives, exercises and worked examples to test and enhance student’s understanding of the material presented in the chapter
- Bolded key terms, with definitions and Glossary for quick referral
- expanded Appendices include a brief reference list of some common computational formulas and examples.
- a Glossary of key terms has been added at the end of the book, with references to sections in parenthesis.
- New online instructor resources for classroom use consisting of test bank questions and Powerpoint slides, plus material on basic math review
