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Introduction to Models

by: Courtney Barnes

Introduction to Models 3100

Courtney Barnes
GPA 3.37

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Powerpoint Lecture
BUsiness Analysis
Class Notes
25 ?




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This 2 page Class Notes was uploaded by Courtney Barnes on Sunday February 14, 2016. The Class Notes belongs to 3100 at Georgia State University taught by Karmakar in Spring 2016. Since its upload, it has received 33 views. For similar materials see BUsiness Analysis in Strategic Communication at Georgia State University.

Similar to 3100 at GSU

Popular in Strategic Communication


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Date Created: 02/14/16
Business Analysis 7 Steps of Problem Solving: 1. Define the Problem 2. Determine the set of alternative solutions 3. Determine the criteria for evaluating alternative 4. Evaluate the alternatives 5. Choose an alternative (make a decision) 6. Implement the second alternative 7. Evaluate the results Qualitative Analysis  Manager’s judgment and experience, including their intuitive “feel” for the problem  More art than a science, concentrating on the quantitative facts associated with the data  Models describe the objectives and relationships that exists resulting in a quantitative method to make a recommendation o Steps:  Model development Advantages o General, less time, less risk, less expensive Types: Physical (Iconic): physical replica of real objects  Tangible, easy comprehension, difficult duplication/share/modify/manipulate, lowest scope of use  EX: model air plane, house/bridge/city Analog: physical in form but not exact replica of object  Intangible, harder comprehension, easy duplication/share/modify/manipulate, wider scope of use  EX: road map, speedometer Mathematical: a system of mathematic formulas and expressions based on key assumptions, estimates, and analysis  Intangible, hardest comprehension, easiet duplication/share/modify/manipulate, widest scope of use  EX: simulation algebraic, spreadsheet  Data preparation  Models allow communication of your ideas and understanding to facilitate teamwork.  Selctively describe the managerial situation. Designate decision variables. Designate performance measures that reflect objectives  Model solution  Report generation Deductive Modeling (Data Poor)  Focuses on variables before data are collected.  Based on assumptions about algebraic relationships & values of the parameters Inferential Modeling (Data Rich)  Focuses on variables as reflected in existing data based on analysis of data to determine relationships and estimate values of parameters Deterministic & Probabilistic Models Deterministic Probabilistic Known with certainty Not know with certainty Many decisions & constraints Few or no constraints Few uncontrolled model inputs that are Uncertainty is incorporated with uncertain. Incorporates constraints on “Random” variables variables Software is available to optimize Used for strategic decision making constrained models involving an org’s relationship to environment Model Build Steps: 1. Study the environment 2. Formulate & construct the model a. Black Box & influence diagrams 3. Do the Math – develop the mathematical relationships in excel Summary: Model – carefully selected abstraction of reality Helpfulness? Allows a run-through of situation Types of Models? Physical (iconic), analog, and mathematical (symbolic) Exogenous = Quantitative values determined outside of the symbolic model (inputs) Endogenous = Quantitative values determined by relationships of symbolic model (outputs)


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