Main description:

The new edition of An Introduction to Statistical Concepts is designed to help students really understand statistical concepts, the situations in which they can be used, and how to apply them to data.

Hahs-Vaughn and Lomax discuss the most popular, along with many of the lesser-known, procedures and models, whilst also exploring nonparametric procedures used when standard assumptions are violated. They provide in-depth coverage of testing assumptions and highlight several online tools for computing statistics (e.g., effect sizes and their confidence intervals and power). This comprehensive, flexible, and accessible text includes a new chapter on mediation and moderation; expanded coverage of effect sizes; and discussions of sensitivity, specificity, false positive, and false negative, along with using the receiver operator characteristic (ROC) curve. In addition to instructions and screen shots for using SPSS, new to this edition is annotated script for using R.

This book, noted for its crystal-clear explanations, and its inclusion of only the most crucial equations, is an invaluable resource for students undertaking a course in statistics in any number of social science and behavioral disciplines-from education, business, communication, exercise science, psychology, sociology and more.

Contents:

Preface

Acknowledgements

1. INTRODUCTION

2. DATA REPRESENTATION

3. UNIVARIATE POPULATION PARAMETERS AND SAMPLE STATISTICS

4. THE NORMAL DISTRIBUTION AND STANDARD SCORES

5. INTRODUCTION TO PROBABILITY AND SAMPLE STATISTICS

6. INTRODUCTION TO HYPOTHESIS TESTING: INFERENCES ABOUT A SINGLE MEAN

7. INFERENCES ABOUT THE DIFFERENCE BETWEEN TWO MEANS

8. INFERENCES ABOUT PROPORTIONS

9. INFERENCES ABOUT VARIANCES

10. BIVARIATE MEASURES OF ASSOCIATION

11. ONE-FACTOR ANALYSIS OF VARIANCE - FIXED-EFFECTS MODEL

12. MULTIPLE COMPARISON PROCEDURES

13. FACTORIAL ANALYSIS OF VARIANCE - FIXED-EFFECTS MODEL

14. INTRODUCTION TO ANALYSIS OF COVARIANCE: THE ONE-FACTOR FIXED-EFFECTS MODEL WITH A SINGLE COVARIATE

15. RANDOM- AND MIXED-EFFECTS ANALYSIS OF VARIANCE MODELS

16. HIERARCHICAL AND RANDOMIZED BLOCK ANALYSIS OF VARIANCE MODELS

17. SIMPLE LINEAR REGRESSION

18. MULTIPLE LINEAR REGRESSION

19. LOGISTIC REGRESSION

20. MEDIATION AND MODERATION

Appendix: Tables