![]() ![]() The application of this tool is exemplified using the well-known Michaelis-Menten equation characterizing simple enzyme kinetics. ![]() Every user familiar with the most basic functions of Excel will be able to implement this protocol, without previous experience in data fitting or programming and without additional costs for specialist software. The confidence of best-fit values is then visualized and assessed in a generally applicable and easily comprehensible way. Experimental data in x/y form and data calculated from a regression equation are inputted and plotted in a Microsoft Excel worksheet, and the sum of squared residuals is computed and minimized using the Solver add-in to obtain the set of parameter values that best describes the experimental data. This course is unique in that the weekly assignments are completed in-application (i.e., on your own computer in Excel), providing you with valuable hands-on training.We describe an intuitive and rapid procedure for analyzing experimental data by nonlinear least-squares fitting (NLSF) in the most widely used spreadsheet program. To pass each module, you'll need to pass a mastery quiz and complete a problem solving assignment. The course is organized into 5 Weeks (modules). I hope for you to at least several times in the course say to yourself, "Wow, I hadn't thought of that before!" Given the wide range in experience and abilities of learners, the goal of the course is to appeal to a wide audience. This course is meant to be fun and thought-provoking. In this course (Part 2), you will: 1) learn advanced data management techniques 2) learn how to implement financial calculations in Excel 3) use advanced tools in Excel (Data Tables, Goal Seek, and Solver) to perform and solve "what-if" analyses 4) learn how to create mathematical predictive regression models using the Regression tool in Excel. This course is the second part of a three-part series and Specialization that focuses on teaching introductory through very advanced techniques and tools in Excel. ![]() By the end of this course, you will have the skills and tools to take on the project-based "Everyday Excel, Part 3 (Projects)". This course is aimed at intermediate users, but even advanced users will pick up new skills and tools in Excel. Building on concepts learned in the first course, you will continue to expand your knowledge of applications in Excel. "Everyday Excel, Part 2" is a continuation of the popular "Everyday Excel, Part 1". ![]()
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