Using Statistical Methods to Assess a Surveillance Program

ABSTRACT

Three metrics have been been developed to assess the National Nuclear Security Agency (NNSA) Surveillance Program against its objectives of detecting defects, determining margins and validating predictions. The surveillance metrics use statistical methods and are probabilities or confidences that produce quantitive assessments on a 0 to 1 scale—from no confidence that a given data stream achieves its surveillance program objectives to complete confidence that the data stream fulfills the objectives. These metrics may be compared and rolled up to support NNSA Surveillance Program management decisions.

KEYWORDS:

• Bayesian
• binomial
• capability index
• confidence
• hypergeometric
• hypothesis tests
• normal distribution
• power
• probability
• random sample
• simple linear regression
• risk
• tolerance bound

Additional information

Notes on contributors

R. L. Bierbaum

R. L. Bierbaum is a distinguished member of technical staff. She is a reliability analyst in the Reliability and Electrical Systems Department. She holds a masters degree in electrical engineering from Stanford University.

K. V. Diegert

K. V. Diegert is a retired manager of the Statistics and Reliability Departments. She holds a Ph.D. in operations research from Cornell University. Her career interests included statistical methods for margin, trend, uncertainty, and reliability assessments.

M. S. Hamada

M. S. Hamada is a scientist in the Statistical Sciences Group and holds a Ph.D. in statistics from the University of Wisconsin Madison. He is a Fellow of the American Statistical Association and a senior member of the American Society for Quality. His research interests include design and analysis of experiments, measurement system assessment, quality control, and reliability.

A. V. Huzurbazar

A. V. Huzurbazar, Ph.D., is a research scientist in the Statistical Sciences Group. She is a Fellow of the American Statistical Association, an elected member of the International Statistical Institute, and senior member of the American Society for Quality. Her research interests include flowgraph and multistate models, Bayesian statistics, reliability and industrial statistics.

A. A. Robertson

A. A. Robertson is a principal member of technical staff. She is a currently affiliated with the Reliability and Electrical Systems Department at Sandia, working as a statistician and reliability engineer. She holds an M.S. in statistics and Ph.D. in economics from the University of California Riverside and a B.S. in mechanical engineering from Cal Poly Pomona.