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.
3.2 Changes in discrete and continuous time
Skills You'll Learn
Monte Carlo Method, Microsoft Excel, Linear Programming (LP), Solver
Reviews
BH
Sep 12, 2017
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!
DA
Feb 07, 2017
A particularly useful course. It built on my existing Excel knowledge and "expertise". I really enjoyed it, as all the skills learned in this course can be applied in the real world.
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.
Taught By
Don Huesman
Managing Director, Wharton Online
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