Flexible, affordable statistics education.

Designed to help you master the software you need to enhance your skills and the practical experience you need to get ahead.

facebook LinkedIn twitter Google+ Email

Introduction to Quantitative Risk Analysis



September 12, 2014 to October 10, 2014

Thank you for your submission.

Introduction to Quantitative Risk Analysis

taught by Huybert Groenendaal
and Greg Nolder

Aim of Course:

This course will cover the most important principles, techniques and tools in Quantitative Risk Analysis. The focus of the course is on how to conduct accurate and effective risk analyses, including framing a risk analysis problem, best practices of risk modeling, selecting the appropriate probability distribution, using data and expert opinion, and presenting risk analysis results. In addition, the course will cover an introduction to probability and statistics theory and various stochastic processes, which is critically important to a solid understanding of quantitative risk analysis.

The course will also familiarize participants with risk analysis modeling environments in Excel (course participants can use @RISK from Palisade, Crystal Ball from Oracle, or ModelRisk from Vose Software), but the lessons and techniques apply equally well to other modeling environments). The course will also cover common mistakes made when doing quantitative risk analysis and how to avoid them.

Course Program:

WEEK 1: Introduction to Risk Analysis

  • Core ideas of risk analysis
  • Going from data to knowledge to a decision-making tool
  • Introduction to statistical descriptors
    • Mean, mode, standard deviation, skewness, kurtosis, percentiles
  • Probability concepts

WEEK 2: Probability Theory

  • Graphical representations of risk events: Venn diagrams, fault trees and event trees
  • Introduction to risk modeling
    • Monte Carlo simulation, ModelRisk, @RISK, Crystal Ball and Excel
    • Brief tutorial on ModelRisk, @RISK, and Crystal Ball
    • Calculation vs. simulation - the pros and cons of Monte Carlo

WEEK 3: Building Risk Analysis Models

  • Most commonly used probability distributions
  • Good practices in risk modeling
  • Common mistakes and how to prevent them

WEEK 4: Presenting Results

  • Typical risk analysis results, their presentation and interpretation
  • Example quantitative risk analyses, including:
  • Project costs risk analysis
    • Engineering
    • Marketing
    • Operations
    • Financial risk analysis
    • Health and Epidemiology


Homework in this course consists of short answer questions to test concepts, guided data analysis problems using software, and guided data modeling problems using software.

In addition to assigned readings, this course also has supplemental readings available online, and short narrated software demos.

Introduction to Quantitative Risk Analysis

Be sure you meet all of the minimum requirements before you register, click here to learn more.


September 12, 2014 to October 10, 2014

Course Fee: $629

Tuition Savings:  When you register online for 3 or more courses, $200 is automatically deducted from the total tuition. (This offer cannot be combined and is only applicable to courses of 3 weeks or longer.)


Have you reviewed the REQUIREMENTS for this course?

Add $50 service fee if you require a prior invoice, or if you need to submit a purchase order or voucher, pay by wire transfer or EFT, or refund and reprocess a prior payment. Please use this printed registration form, for these and other special orders.

Courses may fill up at any time and registrations are processed in the order in which they are received. Your registration will be confirmed for the first available course date, unless you specify otherwise.

Introduction to Quantitative Risk Analysis

taught by Huybert Groenendaal
and Greg Nolder

Who Should Take This Course:

Anyone in business, government and science with an interest in quantitative risk analysis such as professionals needing to perform quantitative risk analysis in areas indcluding, but not limited to, finance, business development, economics, operations, engineering, six sigma, project risk analysis, marketing, epidemiology and microbiology.



These are listed for your benefit so you can determine for yourself, whether you have the needed background, whether from taking the listed courses, or by other experience.

If you are unclear as to whether you have mastered the above requirements, try these placement tests.

All models are developed using Excel, and the following Excel Monte Carlo add-ins: @RISK, Crystal Ball and ModelRisk. It is therefore essential that all participants be reasonably proficient in Excel, including the use of Excel functions.

Organization of the Course:

This course takes place online at the Institute for 4 weeks. During each course week, you participate at times of your own choosing - there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.

The course typically requires 15 hours per week. At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.

Students come to the Institute for a variety of reasons. As you begin the course, you will be asked to specify your category:
  1. You may be interested only in learning the material presented, and not be concerned with grades or a record of completion.
  2. You may be enrolled in PASS (Programs in Analytics and Statistical Studies) that requires demonstration of proficiency in the subject, in which case your work will be assessed for a grade.
  3. You may require a "Record of Course Completion," along with professional development credit in the form of Continuing Education Units (CEU's).  For those successfully completing the course, 5.0 CEU's and a record of course completion will be issued by The Institute, upon request.

Course Text:

Course participants will be provided with weekly digital reading material, as well as the required course text.   Depending on the preferred Monte Carlo simulation Excel add-in, the following three texts can be used:

  1. For ModelRisk, the text is freely available at http://www.vosesoftware.com/vosesoftware/ModelRiskHelp/
  2. For @RISK, the course text is ModelAssist for @RISK, which is freely available at http://www.epixanalytics.com/ModelAssist.html
  3. For Crystal Ball, the course text is ModelAssist for Crystal Ball, which is freely available at http://www.epixanalytics.com/ModelAssist.html

Note that this training package/online book is separate from the course software packages (see note about @RISK, Crystal Ball and ModelRisk below). There is also an optional recommended text, for those needing to retain a reference book after the course: Risk Analysis: A Quantitiative Guide by David Vose, from Wiley. Wiley typically offers statistics.com customers up to 15% discount on this book (and all other statistics titles): enter the code aff15 in the Promotion Code field when prompted during checkout and click the Apply Discount button. (If you are located in Asia, the web procedure for your location may not accept this discount -- try calling your regional Wiley representative.)


Assignments in this course will require the use of spreadsheet-based Monte Carlo simulation software. Course illustrations and homework assignments will use @RISK, Crystal Ball and ModelRisk. Illustrations and model homework answers will be available for these three programs, but the instructors will be able to answer questions about all three packages. @RISK, Crystal Ball and ModelRisk will be made available to course participants at no charge - download instructions and a limited time free demo license will be provided to all course participants at the start of the course.

Want to be
notified of future
course offerings?
Please enter first name.
Please enter last name.
Please enter valid E-mail.
See also the following related courses:

Students comment on our courses:

© statistics.com 2004-2014