Quantitative Methods for Business Decisions

By: David Eadson, Roger Slater, Jon Curwin

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Paperback | 20 January 2013 | Edition Number 7

At a Glance

Paperback
606 Pages

Edition Type
Revised

Dimensions(cm)
25.3 x 19.0 x 2.4

Paperback

$218.75

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This established and popular text is regarded as one of the clearest and most comprehensive in its field. David Eadson has joined Jon Curwin and Roger Slater in the author team, and together they have sought to offer a more compact book with all the qualities of the previous six editions, whilst strengthening the links to online support materials. The new edition has been enhanced to reflect the latest learning plans and techniques, providing students with all the tools they need to pass the typical Quantitative Methods course. Each chapter focuses on a selection of statistical techniques, illustrated with examples from across business, marketing, economics, finance, and public administration, to appeal to students across the business spectrum. Whilst all core material is covered in the book itself, the online offering has been bolstered to include Parts 6-8 covering 'Modelling', 'Mathematical Topics' and 'Student Guides' respectively, in addition to a wide range of other resources including datasets and extra learning tools. Visual signposts throughout the text guide the student to the online platform to provide a seamless interaction between the two this providing a multi-faceted learning experience. The wide-ranging coverage provided makes this the ideal text for the teaching of quantitative methods across all business disciplines at undergraduate, MBA, and post-experience levels.

Industry Reviews

1 BASIC MATHEMATICS. 1A. Mathematical Background. 1B. Financial Mathematics. Part 1: UNDERSTANDING QUANTITATIVE INFORMATION. 2. The quantitative approach. 3. Managing data. 4. Survey methods. Part 2: DESCRIBING DATE. 5. Presentation of data. 6. Measures of location. 7. Measures of dispersion. 8. Index numbers. Part 3: MEASURING UNCERTAINTY. 9. Probability. 10. Discrete probability distributions. 11. The Normal distribution. Part 4: USING STATISTICAL INFERENCE. 12. Samples, Estimation and Confidence intervals. 13. Significance testing. 14. Non-parametric tests. Part 5: RELATING VARIABLES AND PREDICTING OUTCOMES. 15. Correlation and simple regression analysis. 16. Multiple Regression Analysis. 17. Time series.

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