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Title: Graphics to facilitate informative discussion and team decision making

Journal Article · · Applied Stochastic Models in Business and Industry
DOI:https://doi.org/10.1002/asmb.2325· OSTI ID:1438354
 [1];  [2]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. Univ. of South Florida, Tampa, FL (United States). Dept. of Mathematics and Statistics

Everyone knows the expression “A picture is worth a thousand words,” and this effectively summarizes the ability of graphical summaries to convey information and persuade. However, in many cases, the goal for the right visualization is to encourage and guide discussion while helping focus a team to make carefully considered, defensible, and data-driven decisions. The aims of graphics differ if we are trying to communicate the merits of a single choice versus outlining several contending alternatives for further comparison and discussion. These choices each have their own strengths and weaknesses depending on how we value different criteria. They also serve different purposes at various stages of decision making. Often the role of statisticians is not to provide a single answer but to provide rich information and summaries in a manageable and compact form to enable productive discussion among team members. Through a series of diverse examples, this work present principles and strategies for encouraging discussion and informed decision making and discuss how they can be integrated with versatile use of graphical tools for examining multiple objectives, framing trade-offs between alternatives, and examining the impact of subjective priorities and uncertainty on the final decision.

Research Organization:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
AC52-06NA25396
OSTI ID:
1438354
Report Number(s):
LA-UR-17-22524
Journal Information:
Applied Stochastic Models in Business and Industry, Vol. 34, Issue 6; ISSN 1524-1904
Publisher:
WileyCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 8 works
Citation information provided by
Web of Science

References (19)

Bayesian Stockpile Reliability Methodology for Complex Systems journal March 2007
Reliability Modeling using Both System Test and Quality Assurance Data journal June 2008
Optimization of Designed Experiments Based on Multiple Criteria Utilizing a Pareto Frontier journal November 2011
Prediction of Reliability of an Arbitrary System from a Finite Population journal December 2010
A Class of Three-Level Designs for Definitive Screening in the Presence of Second-Order Effects journal January 2011
Some Practical Guidelines for Effective Sample Size Determination journal August 2001
Fraction of Design Space to Assess Prediction Capability of Response Surface Designs journal October 2003
Rethinking the Optimal Response Surface Design for a First-Order Model with Two-Factor Interactions, When Protecting against Curvature journal July 2012
A case study to demonstrate a Pareto Frontier for selecting a best response surface design while simultaneously optimizing multiple criteria: L. LU, C. M. ANDERSON-COOK AND T. J. ROBINSON
  • Lu, Lu; Anderson-Cook, Christine M.; Robinson, Timothy J.
  • Applied Stochastic Models in Business and Industry, Vol. 28, Issue 3 https://doi.org/10.1002/asmb.940
journal March 2012
Balancing Multiple Criteria Incorporating Cost using Pareto Front Optimization for Split-Plot Designed Experiments: Pareto Front Optimization for Split-Plot Designs journal December 2012
Simultaneous Optimization of Several Response Variables journal October 1980
A Case Study on Selecting a Best Allocation of New Data for Improving the Estimation Precision of System and Subsystem Reliability Using Pareto Fronts journal November 2013
Optimal designed experiments using a Pareto front search for focused preference of multiple objectives journal March 2014
Process Optimization for Multiple Responses Utilizing the Pareto Front Approach journal May 2014
Incorporating response variability and estimation uncertainty into Pareto front optimization journal October 2014
Multiple Response Optimization for Higher Dimensions in Factors and Responses: Multiple Response Optimization for Higher Dimensions journal July 2016
Prioritization of stockpile maintenance with layered Pareto fronts journal December 2017
Statistical Engineering—Forming the Foundations journal April 2012
Statistical Engineering—Roles for Statisticians and the Path Forward journal April 2012

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