Statistical Methods for Business and Economics

1st Edition
0077109872 · 9780077109875
This brand new book in statistics aims to provide an introduction to the key methods and techniques essential to a typical statistics syllabus, whilst also helping students to develop the skills needed to analyse, interpret and prepare data for use i… Read More
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Detailed table of contents

Preface

Guided Tour

Technology to enhance teaching and learning

1 Introduction and basic concepts

Part 1 Descriptive Statistics

2. Tables and graphs

3. Measures of location

4. Measures of variation

5. Pairs of variables

Part 2 Probability

6. Definitions of Probability

7. Calculation of probabilities

8. Probability distribution, expectation, variance

9. Families of discrete distributions

10. Families of continuous distributions

11. Joint probability distributions

Part 3 Sampling theory

12. Random samples

13. The sample mean

14. Sample proportion and other sample statistics

Part 4 Inferential statistics

15. Interval estimation and hypothesis testing: a general introduction

16. Confidence intervals and tests for and

17. Statistical inference about

18. Confidence intervals and tests to compare two parameters

19. Simple linear regression

20. Multiple linear regression: introduction

21. Multiple linear regression: extension

22. Multiple linear regression: model violations

23. Time series and forecasting

24. Chi-squared tests

25. Nonparametric statistics

Appendix A1 Excel and SPSS (on Internet)

Appendix A2 Summation operator ?

Appendix A3 Greek letters

Appendix A4 Tables

Appendix A5 Numeric answers of exercises

This brand new book in statistics aims to provide an introduction to the key methods and techniques essential to a typical statistics syllabus, whilst also helping students to develop the skills needed to analyse, interpret and prepare data for use in business, economics and related disciplines.

Covering the essential methods required at undergraduate level, the book is structured into four parts that deal with descriptive statistics, probability, sample theory and inferential statistics, taking students from the basics through to more advanced topics such as multiple linear regression.

Every chapter contains clear descriptions of each technique, illustrated with numerous worked examples to aid students in understanding how to practice statistical methods. The real data used in the examples is drawn from European sources. The text also contains longer case examples set in a European business context, to show how statistics is used everyday in the business environment. Finally, each chapter concludes with a variety of exercises to test students’ ability to apply the theory and attain a high level of competence in using statistics.

This comprehensive book is ideal for student of statistics at undergraduate level taking an introductory module in the topic.

Packed with real life examples that help students to apply statistics in a European business and economic context. Examples range from economic data such gender gap employment rates worldwide, GDP growth in the EU, the size of households in Denmark, to financial examples such as share prices of Eriksson versus Carlsberg, plus thought-provoking problems such as how to compare women and men’s world record performances in athletics.
Application to Excel throughout for business students plus references to key techniques in SPSS, allowing flexibility depending on the software used in class by students learning statistics.
Extensive end of chapter exercises- A typical chapter concludes with over 20 exercises for students to test their ability, with real data provided in the text for students to practice their problem-solving skills. Each chapter includes problems which can be done using software such as Excel.
End of chapter summaries recap the main topics, and key symbols, formulae and terms are also listed for quick student revision
Comprehensive coverage- from a basic introduction through to multiple linear regression and nonparametric statistics, this 25-chapter text provides flexibility to the lecturer to choose their topic coverage based on the requirements of their module and the needs and abilities of their students.