Fitting Mathematical Models to Experimental Data with Excel

In this book, the author offers a practical, step-by-step guide to understanding and applying regression analysis through the accessible power of Excel for students, researchers, and professionals, especially those in the life sciences and engineering fields. Whether you are just beginning your journey with data analysis or looking to enhance your existing skills, this book teaches you how to fit linear, curvilinear, and nonlinear models to real-world data using Excel’s built-in functions and formulas. From simple correlation to advanced topics like Monte Carlo methods, and model comparison, each concept is illustrated with hands-on examples and clear explanations. This book is ideal for anyone modeling real-world data in an academic or professional setting. This comprehensive guide also introduces R-BioXL and ÖK-BUZ GRoFiT (two user-friendly Excel-based tools) designed to streamline biological data analysis, including applications in drug and food degradation kinetics, microbial growth, microbial inactivation and enzyme kinetics. With 14 structured chapters, 48 worked examples and over 40 exercises with solutions, this book is also perfectly suited as a one-semester course textbook. No programming skills are required – just Excel and curiosity.