Linda Nozick is Professor and Director of Civil and Environmental Engineering at Cornell University. She is co-founder and a past director of the College Program in Systems Engineering and has been the recipient of several awards, including a CAREER award from the National Science Foundation and a Presidential Early Career Award for Scientists and Engineers from President Clinton for “the development of innovative solutions to problems associated with the transportation of hazardous waste.” Dr. Nozick has authored over 60 peer-reviewed publications, many focused on transportation, the movement of hazardous materials, and the modeling of critical infrastructure systems. She has been an associate editor for Naval Research Logistics and a member of the editorial board of Transportation Research Part A. Dr. Nozick has served on two National Academy Committees to advise the U.S. Department of Energy on renewal of their infrastructure. During the 1998-1999 academic year, she was a Visiting Associate Professor in the Operations Research Department at the Naval Postgraduate School in Monterey, California. Dr. Nozick holds a B.S. in Systems Analysis and Engineering from the George Washington University and an MSE and Ph.D. in Systems Engineering from the University of Pennsylvania.
Evaluating risk can feel difficult without the proper statistical techniques in your toolbelt. To give yourself that foundation, you will need to understand both the concepts and the tools involved in the process.
In this course, you will walk through the process of risk assessment using several statistical techniques. You will begin by learning to monitor and analyze variations to ensure product or service quality. You will then practice evaluating risk using discrete distributions and summarizing findings using common statistical techniques for risk analysis, including skewness and distributions such as log-normal distributions. You will also gain familiarity with critical functions and concepts in risk analysis, including power law functions and distributions, semi-variance, volatility and beta, and value at risk (VaR), a financial metric used to assess potential asset or portfolio losses. Finally, you will examine design methodologies geared toward improving product reliability, including design for reliability, design for Six Sigma, and quality control. By the end of this course, you will be well-equipped to analyze and evaluate risk using numerous statistical methods.
You are required to have completed the following course or have equivalent experience before taking this course:
- Risk Analysis Foundations
Key Course Takeaways
- Apply measures to characterize statistical distributions and describe the subtleties in different measures of risk
- Apply modeling tools for risk quantification and minimization, including failure mode and effects analysis (FMEA)
- Conduct a failure mode and effects analysis (FMEA)
- Identify key measures that are relevant to evaluating the risk in a given situation
- Apply quality control metrics to detect out-of-control production with control charts and natural process variation
How It Works
Who Should Enroll
- Risk managers and analysts
- Finance and insurance professionals
- Project managers
- Supply chain managers
- Computer and information security engineers
- Software developers
- Professionals across industries interested in understanding risk management