Useful quantitative models help you to make informed decisions both in situations in which the factors affecting your decision are clear, as well as in situations in which some important factors are not clear at all. In this course, you can learn how to create quantitative models to reflect complex realities, and how to include in your model elements of risk and uncertainty. You’ll also learn the methods for creating predictive models for identifying optimal choices; and how those choices change in response to changes in the model’s assumptions. You’ll also learn the basics of the measurement and management of risk. By the end of this course, you’ll be able to build your own models with your own data, so that you can begin making data-informed decisions. You’ll also be prepared for the next course in the Specialization.
Este curso forma parte de Programa Especializado - Business and Financial Modeling
Modeling Risk and Realities
ofrecido por
Acerca de este Curso
4.6
1,241 calificaciones
Habilidades que obtendrás
ModelingRiskMicrosoft ExcelSimulation
Programa - Qué aprenderás en este curso
Semana
1Week 1: Modeling Decisions in Low Uncertainty Settings
This module is designed to teach you how to analyze settings with low levels of uncertainty, and how to identify the best decisions in these settings. You'll explore the optimization toolkit, learn how to build an algebraic model using an advertising example, convert the algebraic model to a spreadsheet model, work with Solver to discover the best possible decision, and examine an example that introduces a simple representation of risk to the model. By the end of this module, you'll be able to build an optimization model, use Solver to uncover the optimal decision based on your data, and begin to adjust your model to account for simple elements of risk. These skills will give you the power to deal with large models as long as the actual uncertainty in the input values is not too high.
4 videos (Total 60 minutos), 2 readings, 1 quiz
4 videos
1.1 How To Build an Optimization Model: Hudson Readers Ad Campaign13m
1.2 Optimizing with Solver, and Alternative Data Inputs26m
1.3 Adding Risk: Managing Investments at Epsilon Delta Capital18m
2 lecturas
PDFs of Slides for Week 110m
Excel Files for Week 110m
1 ejercicio de práctica
Week 1: Modeling in Low Uncertainty Quiz20m
Semana
2Week 2: Risk and Reward: Modeling High Uncertainty Settings
What if uncertainty is the key feature of the setting you are trying to model? In this module, you'll learn how to create models for situations with a large number of variables. You'll examine high uncertainty settings, probability distributions, and risk, common scenarios for multiple random variables, how to incorporate risk reduction, how to calculate and interpret correlation values, and how to use scenarios for optimization, including sensitivity analysis and the efficient frontier. By the end of this module, you'll be able to identify and use common models of future uncertainty to build scenarios that help you optimize your business decisions when you have multiple variables and a higher degree of risk.
3 videos (Total 51 minutos), 2 readings, 1 quiz
3 videos
2.2 Common Scenarios for Multiple Random Variables, Risk Reduction, and Calculating and Interpreting Correlation Values18m
2.3 Using Scenarios for Optimizing Under High Uncertainty, Sensitivity Analysis and Efficient Frontier15m
2 lecturas
PDFs of Lecture Slides for Week 210m
Excel Files for Week 210m
1 ejercicio de práctica
Week 2: Modeling in High Uncertainty Quiz20m
Semana
3Week 3: Choosing Distributions that Fit Your Data
When making business decisions, we often look to the past to make predictions for the future. In this module, you'll examine commonly used distributions of random variables to model the future and make predictions. You'll learn how to create meaningful data visualizations in Excel, how to choose the the right distribution for your data, explore the differences between discrete distributions and continuous distributions, and test your choice of model and your hypothesis for goodness of fit. By the end of this module, you'll be able to represent your data using graphs, choose the best distribution model for your data, and test your model and your hypothesis to see if they are the best fit for your data.
4 videos (Total 81 minutos), 2 readings, 1 quiz
4 videos
3.2, pt 1: Choosing Among Distributions: Discrete Distributions25m
3.2, pt 2: Choosing Among Distributions: Continuous Distributions11m
3.3 Hypothesis Testing and Goodness of Fit22m
2 lecturas
PDFs of Lecture Slides for Week 310m
Excel Files for Week 310m
1 ejercicio de práctica
Week 3: Choosing Fitting Distributions Quiz20m
Semana
4Week 4: Balancing Risk and Reward Using Simulation
This module is designed to help you use simulations to enabling compare different alternatives when continuous distributions are used to describe uncertainty. Through an in-depth examination of the simulation toolkit, you'll learn how to make decisions in high uncertainty settings where random inputs are described by continuous probability distributions. You'll also learn how to run a simulation model, analyze simulation output, and compare alternative decisions to decide on the most optimal solution. By the end of this module, you'll be able to make decisions and manage risk using simulation, and more broadly, to make successful business decisions in an increasing complex and rapidly evolving business world.
4 videos (Total 53 minutos), 2 readings, 1 quiz
4 videos
4.2 Connecting Random Inputs and Random Outputs in a Simulation23m
4.3 Analyzing and Interpreting Simulation Output: Evaluating Alternatives Using Simulation Results10m
Course Conclusion25s
2 lecturas
PDFs of Lecture Slides10m
Excel files for Week 410m
1 ejercicio de práctica
Week 4: Using Simulations Quiz20m
20%
comenzó una nueva carrera después de completar estos cursos
21%
consiguió un beneficio tangible en su carrera profesional gracias a este curso
Principales revisiones
por JN•Apr 13th 2018
covers good amount of material and exactly what is in the outline, presented with enough detail to follow. Good walk-through of the spreadsheets helps understanding, easy to follow along and practice.
por LC•Dec 19th 2016
Material was very well presented. Week 3 was challenging, but taking time to print out the slides, work through them rigorously proved very helpful. I found all sections very, very informative.
Instructores
Sergei Savin
Associate Professor of Operations, Information and DecisionsThe Wharton School
Senthil Veeraraghavan
Associate Professor of Operations, Information and DecisionsThe Wharton School
Acerca de Universidad de Pensilvania
The University of Pennsylvania (commonly referred to as Penn) is a private university, located in Philadelphia, Pennsylvania, United States. A member of the Ivy League, Penn is the fourth-oldest institution of higher education in the United States, and considers itself to be the first university in the United States with both undergraduate and graduate studies.
Acerca del programa especializado Business and Financial Modeling
Wharton's Business and Financial Modeling Specialization is designed to help you make informed business and financial decisions. These foundational courses will introduce you to spreadsheet models, modeling techniques, and common applications for investment analysis, company valuation, forecasting, and more. When you complete the Specialization, you'll be ready to use your own data to describe realities, build scenarios, and predict performance.
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.
¿Qué recibiré si me suscribo a este Programa especializado?
Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.
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