Basic Computational Techniques for Data Analysis
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Basic Computational Techniques for Data Analysis
Description
This book is a multi-stage learning resource that takes readers from basic data handling and software orientation to statistical analysis and financial applications using MS Excel and R. Through a gradual, step-by-step approach, it equips readers with the essential skills needed to understand, analyse, and interpret data in today’s data-driven world.
Using clear illustrations, the book enables readers to organise and manage data, perform analytical computations, create meaningful visualisations, and draw conclusions. It introduces core concepts in research, data analysis, and economic and financial decision-making, demonstrating their relevance in academic, professional, and everyday contexts. This book enables readers to:
- Work confidently with MS Excel and R for efficient data handling and analysis
- Present and visualise data using charts, tables, and Pivot Tables
- Apply statistical techniques such as descriptive statistics, correlation, regression, and hypothesis testing
- Perform financial analysis using concepts such as time value of money, compounding, NPV, IRR, and EMI calculations
By combining concepts with practical implementation, the book provides a strong foundation in computational techniques essential for modern data analysis.
This revised third edition introduces two new chapters on R for data analysis, complementing the book’s Excel-based approach, making it an invaluable resource for beginners and students of economics, commerce, management, and the social sciences. This book will be useful for courses in econometrics, financial technology, and applied economics, as it equips readers with the analytical and computational skills required for academic excellence and professional success.
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