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This well-loved textbook covers all of the key quantitative methods needed to solve everyday business problems. Presented in a highly accessible and concise manner, Les Oakshott’s clear and friendly writing style guides students from basic statistics through to advanced topics, such as hypothesis testing and time series, as well as operational research techniques such as linear programming and inventory management. Step-by-step instructions and accompanying activities will help students to practice and gain confidence in carrying out techniques. The book’s coverage is fully grounded within the real world of business. Real-life case studies open every chapter and numerous examples throughout demonstrate why quantitative techniques are needed for a business to be successful.

An ideal textbook for undergraduate students of business, management and finance, it is also suitable for MBA students and postgraduates.

### 1. Revision mathematics

Abstract
The aim of this chapter is to provide the basic numeracy skills that will be needed in subsequent chapters. If you have any doubts about your knowledge of particular areas you are recommended to tackle the diagnostic tests that you will find throughout this chapter.
Les Oakshott

### 2. Keeping up with change: Index numbers

Abstract
An index is a means of comparing changes in some variable, often price over time. This is particularly useful when there are many items involved and when the prices and quantities are in different units.
Les Oakshott

### 3. Collecting data: Surveys and samples

Abstract
Many decisions made by businesses and by the government are the result of information obtained from sample data, as it is often too costly or impractical to collect data for the whole population.
Les Oakshott

### 4. Finding patterns in data: Charts and tables

Abstract
Some understanding of sampling methods (Chapter 3: Collecting data: surveys and samples) would be useful but is not essential.
Les Oakshott

### 5. Making sense of data: Averages and measures of spread

Abstract
In order to fully understand this chapter you should have read Chapter 4 (Finding patterns in data: charts and tables).
Les Oakshott

### 6. Taking a chance: Probability

Abstract
It is difficult to go very far in solving business problems without a basic understanding of probability.
Les Oakshott

### 7. The shape of data: Probability distributions

Abstract
In order to fully understand this chapter you should have read through Chapter 4 (Finding patterns in data: charts and tables), Chapter 5 (Making sense of data: averages and measures of spread) and Chapter 6 (Taking a chance: probability).
Les Oakshott

### 8. Interpreting with confidence: Analysis of sample data

Abstract
In order to fully understand this chapter you should have read through Chapter 3 (Collecting data: surveys and samples) and Chapter 7 (The shape of data: probability distributions).
Les Oakshott

### 9. Checking ideas: Testing a hypothesis

Abstract
To complete this chapter successfully you should have read through Chapter 8 (Interpreting with confidence: analysis of sample data)
Les Oakshott

### 10. Cause and effect: Correlation and regression

Abstract
Knowledge of hypothesis tests (Chapter 9: Checking ideas: testing a hypothesis) would be useful
Les Oakshott

### 11. How to make good decisions

Abstract
To complete this chapter successfully you should have worked through Chapter 6 (Taking a chance: probability).
Les Oakshott

### 12. Choosing wisely: Investment appraisal

Abstract
Companies are frequently faced with the need to decide between a number of investment opportunities. As capital is usually limited, a company will want to choose the ‘best’ project or projects. But what do we mean by ‘best’, and how can we differentiate between different projects that may look equally attractive?
Les Oakshott

### 13. Forecasting: Time series analysis

Abstract
There are no prerequisites for this chapter apart from a basic knowledge of Excel.
Les Oakshott

### 14. Making the most of things: Linear programming

Abstract
There are no prerequisites for this chapter apart from a basic knowledge of Excel.
Les Oakshott

### 15. Planning large projects: Network analysis

Abstract
Network analysis is a branch of mathematics (combinatorial problems) that tries to optimize the flows in a network. This network could be the flow of goods or people between cities (the ‘travelling salesmen problem’) or it could be the scheduling of activities in a construction project. In Chapter 14 we showed how the transportation algorithm could be used to solve particular types of linear programming problems.
Les Oakshott

### 16. Managing stock levels: Materials management and inventory control

Abstract
For part of this chapter you will find it useful to have some knowledge of the normal distribution (see Chapter 7).
Les Oakshott