Quantitative Methods for Business and Economics (Modular Texts In Business & Economics) - Tapa blanda

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Quantitative Methods for Business and Economics 2/e

`...The inclusion of a basic mathematics chapter is an excellent idea. A great strength is the clear explanation of some extremely complex issues with excellent diagrams. In addition, each chapter has a set of `self-check' questions with well explained solutions. I would certainly advise any student on a BTEC or undergraduate course in business studies or business economics to purchase this book.'

Times Higher Education Supplement review February 1999

Building on the strength of the first edition, Quantitative Methods for Business and Economics provides a simple introduction to the mathematical and statistical techniques needed in business. This book is accessible and easy to use, with the emphasis clearly on how to apply quantitative techniques to business situations. It includes numerous real world applications and many opportunities for student interaction. It is clearly focused on business, management and economics students taking a single module in Quantitative Methods.

Key features:

- Concise and accessible introduction to quantitative methods, assuming no prior knowledge
- Interactive approach to engage student interest, including extra website exercises
- Extensive worked examples and self-check exercises to aid self-paced learning
- Fully worked solutions to help demonstrate to students the skills and techniques needed for exam success
- Tight focus on the key topics covered in an introductory course
- Real world applications to help students see the relevance of the topic areas
- Lecturer supplements package: Instructor's Manual, including extra questions and solutions, some involving the use of statistical packages; practice exam papers; PowerPoint slides.

Glen Burton, George Carrol and Stuart Wall are highly experienced lecturers on business economics and quantitative methods at Anglia Polytechnic University. They have taught quantitative methods on a wide range of undergraduate and professional courses, often involving students with little prior knowledge of mathematical and statistical techniques.