This comprehensive text, now in its fifth edition, teaches the reader how to apply the most widely used statistical methods in business. The book gives you the how, what, where, when and why of numbers and statistics. The book has twenty-five chapters divided into seven study areas. Each chapter focuses on a selection of techniques, illustrated with examples from business, marketing, economics, accounting, finance, and public administration. This is viewed as the clearest, most accurate and comprehensive book available in the field of quantitative methods. Now in line with the latest Excel developments, the book should cover the syllabus for a quantitative methods course on a business related degree course, and serve as a core text for professional examinations, and MBA courses.
|Publisher:||Cengage Learning EMEA Higher Education|
|Edition description:||New Edition|
|Product dimensions:||7.40(w) x 9.60(h) x 1.50(d)|
About the Author
Jon Curwin is a Principal Lecturer at the University of Central England Business School.
Roger Slater is Head of the Faculty Resources Centre for the Faculty of Law, Humanities and Social Sciences at the University of Central England, UK, and has been involved in teaching and examining quatitative topics for over 30 years.
Table of Contents
PART 1: QUANTITATIVE INFORMATION. Introduction. Quick Start: Quantitative Information 1. The Quantitative Approach. 2. Managing Data. 3. Survey Methods. 4. Presentation of Data. Part 1 Conclusions PART 2: DESCRIPTIVE STATISTICS. Introduction. Quck Start: Descriptive Statistics 5. Measures of Location. 6. Measures of Dispersion. 7. Index Numbers. Part 2 Conclusions PART 3: MEASURING UNCERTAINTY. Introduction. Quick Start: Measuring uncertainty 8. Probability. 9. Discrete Probability Distributions. 10. The Normal Distribution. Part 3 Conclusions PART 4: STATISTICAL INFERENCE. Introduction Quick start: Inference Quick Start 11. Confidence Intervals. 12. Significance Testing. 13. Non-parametric Tests. Part 4 Conclusions PART 5: RELATING VARIABLES AND PREDICTING OUTCOMES. Quick Start: Relating Variables and predicting outcomes 14. Time Series. 15. Correlation. 16. Regression. 17. Multiple Regression and Correlation. Part 5 Conclusions. PART 6: MODELLING. Introduction. 18. The Time Value of Money. 19. Linear Programming. 20. Networks. 21. Modelling Stock Control and Queues. 22. Simulation. Part 6 Conclusions. PART 7: MATHEMATICAL BACKGROUND. Introduction. 23. Mathematical Relationships. 24. Matrices. 25. Use of Calculus. Conclusions. Appendices.