This book is partly based on lectures the authors give at Sheffield Business School, Sheffield Hallam University between 2010- 2015. It is an exploratory guide to business analysis. It aims to develop foundation knowledge on the techniques behind data analysis and decision making based on information derived from data analysis. It delves into the use of appropriate software tools to analyse data and provides rich examples from real world organisational data sets. The examples are self-contained and easy to interpret, thus giving the learner options to learn freely at a pace they are comfortable.

1. Introduction to fundamental concepts for Business Analysis
   1. What is the point of this book?
   2. Getting to grips with the basics
   3. Working through the basics
   4. Revision section – exercises
   5. Chapter references
2. Decision Making, Data and Information
   1. Decision making
   2. Data and Information
   3. Sources of Data
   4. Collecting Data
   5. Sampling
   6. Information Requirements for Effective Decision Making
   7. Quality of Information
   8. Conclusion
   9. Chapter references
3. Exploring Data; Deriving Information
   1. Introduction
   2. Storing and Structuring Data
   3. The Organisation of Data
   4. Tabulation
   5. Ordering Data
   6. Frequency Distribution
   7. Grouped Frequency Distribution
   8. Cumulative Frequency Distribution
   9. Percentiles
   10. Presenting Information Pictorially
   11. Conclusion
   12. Chapter references
4. Summarising Data
   1. Introduction
   2. Some fundamental concepts for summarising data
   3. Measures of the Typical Value or Average (Measures of Location)
   4. Chapter references
5. Measuring and Evaluating Variation in Data Values
   1. Introduction
   2. Percentage change
   3. Weighted Index Numbers
   4. Deflating a time series – using a value index as a deflator
   5. Chapter references
6. Association between Variables
   1. Introduction
   2. Correlation Analysis
   3. Scatter plot
   4. Strength of the Linear Association – the Correlation Coefficient, r
   5. Regression Analysis
   6. The Coefficient of Determination, r2
   7. Estimation using the Linear Regression Model
   8. Chapter references
7. Time Series and Forecasting
   1. Introduction
   2. Time Series Components
   3. Evaluation and comparison of models
   4. Chapter references
8. Financial Modelling
   1. Introduction
   2. Costs, Revenue, Profit and Contribution
   3. Using a graph to illustrate financial models
   4. Non-linear relationships
   5. Other useful types of business relationships
   6. Chapter references
9. Financial Analysis Money – Interest and Time Value
   1. Introduction
   2. Interest
   3. Applications of interest rate calculations
   4. Present Value
10. Brief concluding remarks and considerations