Quantitative Methods for Business

John Buglear

• Publisher: Routledge
• Year: 2007
• eBook ISBN: 9781136370144
• Topic: Business
• Subtopic: Business General
• Index: Business

Quantitative Methods for Business: The A-Z of QM will enable readers to:
*Appreciate the significance of quantitative methods for businesses and the study of business
*Understand and apply a wide range of quantitative techniques
*Select appropriate quantitative techniques for data analysis, problem solving and decision making
*Interpret and communicate the results of quantitative analysis

1

Chapter

Setting off

Chapter Objectives

This chapter will help you to:

assess the importance businesses attach to quantitative methods

make full use of this book

apply arithmetical procedures

use the technology: calculators and computer software

Beginning a new programme of study is always something of a challenge. To help ease you into the study of quantitative methods this chapter begins with an outline of the importance of numbers in business life. Following that is an overview of this book and ways in which it can assist in your studies. The next section provides guidance on arithmetical procedures that feature in the techniques you will meet in later chapters. The chapter closes with advice on the use of calculators and software that can take the hard graft out of the analysis to allow you to concentrate on interpreting the results.

1.1 Quantitative Methods, Numbers and Business

If you are studying business or interested in any aspect of business you need to know about quantitative methods. Why? Because business is all about quantities: quantities of goods produced and services provided, quantities of inputs and costs, quantities of revenues and profit, and so on.

How many times have you seen a news programme that does not mention numbers? How many times have you read a newspaper in which no numbers are quoted? Numbers are integral to our way of life, our understanding of the world around us. This is especially so of the business world that, now and in the future, we relate to as customers, employees, suppliers.

Consider how numbers played a part in the publisher’s decision to produce this book. They were interested in the size of the potential market, which meant looking at the number of students on business courses. They needed to set a price, which led them to consider the prices of rival texts on the one hand and their own production costs on the other. The production costs would depend in turn on the number of pages in the book and the number of copies to be produced.

You may feel rather uncomfortable at the prospect of studying numerical subjects. Perhaps memories of Maths at school have left a legacy that leads you to associate analysing numbers with mental numbness. If this is what happened to you, it is best to try to put it behind you. For one thing the focus you will find here is on applications and interpretation rather than proof and derivation. It may help to bear in mind that employers consistently identify numerical and problem-solving skills as highly desirable qualities in potential employees, so try to think of your quantitative studies as building a valuable career asset. For example, in graduate recruitment literature the Exxon Mobil Corporation state that ‘Numerical and analytical skills are essential for all vacancies’ (Hobsons, 2002, p. 320).

If you do approach the study of quantitative methods with trepidation you may be tempted to think that this is a subject that really doesn’t matter because it is of no use to businesses. It might be comforting to think that the subject is irrelevant because this would excuse not bothering with it. In fact the subjects that you will meet in this book have in many cases been forged in and grown up with the business world. The origins of many of the techniques described in this book are embedded in the history of business sectors as diverse as brewing and insurance.

This is not an opinion held only by people who teach it; a number of researchers have tried to establish the use that companies make of quantitative methods. Usually these studies are aimed at finding how widespread is the use of a particular type of technique, but occasionally researchers canvass the application of the spectrum of techniques that comprise quantitative methods. One comprehensive study was a survey of American companies undertaken in the 1980s (Kathawala, 1988).

Kathawala surveyed US companies that were in the ‘Fortune 500’. Fortune is an American business magazine that periodically compiles lists of the most prominent companies in the USA. He sent questionnaires to firms in the manufacturing and service sectors, as well as a random sample of small companies. Respondents were asked about the extent to which they used a variety of quantitative techniques.

Thirteen of these techniques feature in this book. Approximately half or more of the respondents’ organizations put the majority of these to moderate, extensive or frequent use. Some were very widely used; in the case of forecasting only 6% of respondents reported little or no use.

Kathawala found that in general large companies were more likely to use quantitative methods than small companies. He also found that some techniques were widely used in certain sectors; for example, all respondents from the retailing sector reported that they used stock control methods, whereas all the life insurance companies said they used computer simulation.

One interesting aspect of Kathawala’s study was the reasons companies gave for not using quantitative techniques. Foremost among these were that managers lacked knowledge of them. In other words, many respondents who reported that particular techniques were not used said that it was because they had no training in them, not that the techniques were considered to be of no value.

The comprehensive nature of the study makes Kathawala’s work interesting, but it is now some years old. However, in the years since it was published the quality and availability of computer software that performs quantitative analysis has vastly improved, suggesting that the use to which businesses put quantitative methods has increased rather than decreased.

1.2 Using this Book

This first chapter constitutes a prologue or launch pad for your studies. It is designed to help you start with an idea of the relevance of the subject, an outline of the structure and approach used in this book, and what might be termed a refresher course in the basic ‘tools of the trade’.

Chapters 2 and 3 cover simple deterministic models that can help to represent and understand business operations. The term deterministic is used because the numbers used in such models are fixed or predetermined. Chapters 4 to 9 introduce descriptive techniques, methods that will enable you to arrange or analyse sets of figures in ways that help to describe the situation being studied. These are important because typically figures do vary and the way in which they vary is of interest.

Chapters 10 to 14 deal with techniques and models that allow the risk inherent in business situations to be reflected in the analysis of them. Chapters 15 to 17 are about inferential techniques, methods that enable you to make inferences or draw conclusions about an issue in general based on the study of a comparatively modest amount of data.

The final chapter is designed to help you tackle numerical aspects of the sort of project or dissertation that you will probably be asked to write towards the end of your course.

The book will introduce you to a variety of analytical techniques drawn from the fields of Business Mathematics, Operational Research and Statistics that together constitute a ‘tool-kit’ of methods that can be used to investigate situations and help solve problems. Like any other tool-kit, the key to using it properly is to know not only what each tool does, but also how and when to use it. The book will help you develop this ability by illustrating the application of the methods described using business contexts.

To help you appreciate the wider relevance of the methods you will meet, there are sections identified as Road tests. These are outlines of appli...

Table of contents

• Cover
• Half Title
• Title Page
• Copyright
• Contents
• Preface
• Acknowledgements
• Chapter 1. Setting off
• Chapter 2. Getting linear models straight
• Chapter 3. Dealing with curves without going round the bend
• Chapter 4. Filling up – fuelling quantitative analysis
• Chapter 5. Good visibility – pictorial presentation of data
• Chapter 6. General directions – summarizing data
• Chapter 7. Two-way traffic – summarizing and representing relationships between two variables
• Chapter 8. Counting the cost – summarizing money variables over time
• Chapter 9. Long distance – analysing time series data
• Chapter 10. Is it wor th the risk? – introducing probability
• Chapter 11. Finding the right way – analysing decisions
• Chapter 12. Accidents and incidence – discrete probability distributions and simulation
• Chapter 13. Smooth running – continuous probability distributions and basic queuing theory
• Chapter 14. Getting from A to B – project planning using networks
• Chapter 15. Taking short cuts – sampling methods
• Chapter 16. Test driving – sampling theory, estimation and hypothesis testing
• Chapter 17. High performance – statistical inference for comparing population means and bivariate data
• Chapter 18. Going off-road – managing quantitative research for projects and dissertations
• Appendix 1. Statistical and accounting tables
• Appendix 2. Answers and selected worked solutions to review questions
• References
• Index