Simulation Modeling in Excel | Understanding Probability Distributions for Better Decision-Making
Автор: Business Courses
Загружено: 2025-05-22
Просмотров: 12
#SimulationModeling #ExcelSimulation #ProbabilityDistributions #MonteCarloSimulation #ExcelTutorial #BusinessAnalytics #RiskModeling #WhatIfAnalysis #OperationsResearch #ExcelForBusiness #DataDrivenDecisions #FlawOfAverages #SpreadsheetModeling #ExcelRandomNumbers
In this video, we dive deep into the world of simulation modeling using Excel, focusing on how to incorporate uncertainty into your models using probability distributions. Whether you're a student, analyst, or business professional, this tutorial will help you understand how to simulate real-world scenarios and make smarter, data-driven decisions.
🔍 What You’ll Learn:
What is a simulation model and how it differs from traditional models
How to use random numbers and probability distributions in Excel
The difference between discrete and continuous distributions
How to model uncertainty using normal, triangular, uniform, and binomial distributions
The concept of the flaw of averages and why it matters
How to use Excel functions like =RAND() and tools like @RISK for simulation
📊 This video is perfect for:
Business analysts and data scientists
Students in operations research, statistics, or finance
Anyone interested in what-if analysis and risk modeling
💡 Learn how simulation helps answer critical business questions without changing real-world systems—and how to avoid common pitfalls in modeling uncertainty.
📌 Tools & Resources Used:
Microsoft Excel
ProbabilityDistributions.xlsx
@RISK (optional for advanced users)
Reference: Business Analytics
ISBN: 9781305947542
Author: Albright/Winston
Published by: Cengage
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