The simple spreadsheet is one of the most powerful data analysis tools that exists, and it’s available to almost anyone. Major corporations and small businesses alike use spreadsheet models to determine where key measures of their success are now, and where they are likely to be in the future. But in order to get the most out of a spreadsheet, you have the know-how to use it. This course is designed to give you an introduction to basic spreadsheet tools and formulas so that you can begin harness the power of spreadsheets to map the data you have now and to predict the data you may have in the future. Through short, easy-to-follow demonstrations, you’ll learn how to use Excel or Sheets so that you can begin to build models and decision trees in future courses in this Specialization. Basic familiarity with, and access to, Excel or Sheets is required.
2.2 Structuring a spreadsheet to model variables, objectives, and objective functions
Destrezas que aprenderás
Monte Carlo Method, Microsoft Excel, Linear Programming (LP), Solver
Reseñas
So many tools that I knew existed and have tried to use the How-To's to learn how they work and until the Prof takes you through them one-at-a-time, they never make sense. Great Stuff!
The course was exceptional. I learnt a lot about excel and google sheet from this course. The instructor has been very smooth and clear in teaching his concepts. I am deeply grateful.
In this module, you'll move from spreadsheet to model, so you can begin to create your own models that reflect real-world events. You'll learn how to organize and lay out model elements, as well as the types of objective functions and their use. You'll also learn what-if analysis and scenarios, sensitivity analysis, and other classic models. By the end of this module, you'll be able to design a spreadsheet reflecting assumptions, decision variables, and outcomes, create a basic cashflow model, evaluate a small business opportunity, conduct what-if analysis, identify key variables using sensitivity analysis, and linear programming models and deterministic models.
Impartido por:
Don Huesman
Managing Director, Wharton Online
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