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University of Pennsylvania

Introduction to Spreadsheets and Models

University of Pennsylvania via Coursera

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Overview

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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.

Syllabus

  • Spreadsheets: A Tool for Thinking with Numbers
    • This module was designed to introduce you to the history of spreadsheets, their basic capabilities, and how they can be used to create models. You'll learn the different types of data used in spreadsheets, spreadsheet notations for mathematical operations, common built-in formulas and functions, conditional expressions, relative and absolute references, and how to identify and correct circular references. By the end of this module, you'll understand the context of spreadsheets, be able to navigate a spreadsheet, use built-in formulas and functions in spreadsheets, create your own simple formulas, and identify and correct common errors so you can put spreadsheets to work for you.
  • From Spreadsheet to Model
    • 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.
  • Addressing Uncertainty and Probability in Models
    • This module was designed to introduce you to how you can use spreadsheets to address uncertainty and probability. You'll learn about random variables, probability distributions, power, exponential, and log functions in model formulas, models for calculating probability trees and decision trees, how to use regression tools to make predictions, as well as multiple regression. By the end of this module, you'll be able to measure correlations between variables using spreadsheet statistical functions, understand the results of functions that calculate correlations, use regression tools to make predictions, and improve forecasts with multiple regression.
  • Simulation and Optimization
    • In this module, you'll learn to use spreadsheets to implement Monte Carlo simulations as well as linear programs for optimization. You'll examine the purpose of Monte Carlo simulations, how to implement Monte Carlo simulations in spreadsheets, the types of problems you can address with linear programs and how to implement those linear programs in spreadsheets. By the end of this module, you'll be able to model uncertainty and risk in spreadsheets, and use Excel's solver to optimize resources to reach a desired outcome. You'll also be able to identify the similarities and differences between Excel and Sheets, and be prepared for the next course in the Business and Financial Modeling Specialization.

Taught by

Don Huesman

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Reviews

4.2 rating, based on 6 Class Central reviews

4.2 rating at Coursera based on 3805 ratings

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  • Anonymous
    This Course was Informative with lots of examples .. It can be applied on my work culture and it will be helpful in future
  • Peter Adamko
  • Richard Esperon
  • Marek Prokop
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