RStudio for Six Sigma - Monte Carlo Simulation

Offered By
Coursera Project Network
In this Guided Project, you will:

Generate Continuous, Discrete and Categorical Data (Xs) Using Statistical Distributions

Create A Transfer Function That Relates The Xs With The Y (Dependent Variable)

Perform Monte Carlo Simulation & Sensitivity Analysis Using RStudio

Clock2 hours
BeginnerBeginner
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

In this 2-hour long project-based course, you will learn how to 1. Generate Continuous, Discrete and Categorical Data (Xs) Using Statistical Distributions 2. Create A Transfer Function That Relates The Xs With The Y (Dependent Variable) 3. Perform Monte Carlo Simulation & Sensitivity Analysis Using RStudio Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Skills you will develop

R ProgrammingData AnalysisMonte Carlo MethodSix SigmaRstudio

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Random Generation of Categories & Integers Based On Uniform, Binomial, Poission and User Defined Statistical Distributions using RStudio.

  2. Random Generation of Continuous Data Based On Uniform, Normal, Log-normal, Exponential, Gamma and Triangular Statistical Distributions using RStudio.

  3. Example 1: Development of a Transfer Function Linking Xs with Y, and Perform Monte Carlo Simulation

  4. Example 2: Develop Transfer Function Using RStudio's "Function" Feature. Peform Monte Carlo Simulation.

  5. Perform Sensitivity Analysis Using Two Approaches. (A) Sensitivity of a Transfer Function at given Xs. (B) Sensitivity Analysis over a range of Simulated Xs.

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

Frequently asked questions

Frequently Asked Questions

More questions? Visit the Learner Help Center.