Les Oakshott is a former Associate Fellow of Warwick Business School, UK.Kathy Kotiadis is Professor of Management Science/Operational Research at the University of Kent, UK.

• Part I: Mathematical Applications1. Revision Mathematics2. Keeping up with Change: Index NumbersPart II: Collecting and Interpreting Data3. Collecting Data: Surveys and Samples4. Finding Patterns in Data: Charts and Tables5. Making Sense of Data: Averages and Measures of SpeedPart III: Probability and Statistics6. Taking a Chance: Probability7. The Shape of Data: Probability Distributions8. Interpreting with Confidence: Analysis of Sample Data9. Checking Ideas: Testing a Hypothesis10. Cause and Effect: Correlation and RegressionPart IV: Decision-Making Techniques11. How to Make Good Decisions12. Choosing Wisely: Investment Appraisal13. Forecasting: Time Series Analysis14. Making the Most of Things: Linear Programming15. Planning Large Projects: Network Analysis16. Managing Stock Levels: Materials Management and Inventory ControlBibliographyAppendix: Statistical TablesIndex

A cornerstone text that every data science and analytics student should have on their shelf. Oakshott and Kotiadis strike the perfect balance between mathematical rigour and real-world applicability, making complex quantitative methods genuinely accessible.

Les Oakshott is a former Associate Fellow of Warwick Business School, UK.Kathy Kotiadis is Professor of Management Science/Operational Research at the University of Kent, UK.

• Part I: Mathematical Applications1. Revision Mathematics2. Keeping up with Change: Index NumbersPart II: Collecting and Interpreting Data3. Collecting Data: Surveys and Samples4. Finding Patterns in Data: Charts and Tables5. Making Sense of Data: Averages and Measures of SpeedPart III: Probability and Statistics6. Taking a Chance: Probability7. The Shape of Data: Probability Distributions8. Interpreting with Confidence: Analysis of Sample Data9. Checking Ideas: Testing a Hypothesis10. Cause and Effect: Correlation and RegressionPart IV: Decision-Making Techniques11. How to Make Good Decisions12. Choosing Wisely: Investment Appraisal13. Forecasting: Time Series Analysis14. Making the Most of Things: Linear Programming15. Planning Large Projects: Network Analysis16. Managing Stock Levels: Materials Management and Inventory ControlBibliographyAppendix: Statistical TablesIndex

A cornerstone text that every data science and analytics student should have on their shelf. Oakshott and Kotiadis strike the perfect balance between mathematical rigour and real-world applicability, making complex quantitative methods genuinely accessible.

Les Oakshott is a former Associate Fellow of Warwick Business School, UK.Kathy Kotiadis is Professor of Management Science/Operational Research at the University of Kent, UK.

• Part I: Mathematical Applications1. Revision Mathematics2. Keeping up with Change: Index NumbersPart II: Collecting and Interpreting Data3. Collecting Data: Surveys and Samples4. Finding Patterns in Data: Charts and Tables5. Making Sense of Data: Averages and Measures of SpeedPart III: Probability and Statistics6. Taking a Chance: Probability7. The Shape of Data: Probability Distributions8. Interpreting with Confidence: Analysis of Sample Data9. Checking Ideas: Testing a Hypothesis10. Cause and Effect: Correlation and RegressionPart IV: Decision-Making Techniques11. How to Make Good Decisions12. Choosing Wisely: Investment Appraisal13. Forecasting: Time Series Analysis14. Making the Most of Things: Linear Programming15. Planning Large Projects: Network Analysis16. Managing Stock Levels: Materials Management and Inventory ControlBibliographyAppendix: Statistical TablesIndex

A cornerstone text that every data science and analytics student should have on their shelf. Oakshott and Kotiadis strike the perfect balance between mathematical rigour and real-world applicability, making complex quantitative methods genuinely accessible.