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
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.
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