A Reliability Assurance Test Planning and Analysis Tool

This presentation documents the work of IDA 2024 Summer Associate Emma Mitchell. The work presented details an R Shiny application developed to provide a user-friendly software tool for researchers to use in planning for and analyzing system reliability. Specifically, the presentation details how one can plan for a reliability test using Bayesian Reliability Assurance test methods. Such tests utilize supplementary data and information, including reliability models, prior test results, expert judgment, and knowledge of environmental conditions, to plan for reliability testing, which in turn can often help in reducing the required amount of testing....

2024 · Emma Mitchell, Rebecca Medlin, John Haman, Keyla Pagan-Rivera, Dhruv Patel

Introduction to Human-Systems Interaction in Operational Test and Evaluation Course

Human-System Interaction (HSI) is the study of interfaces between humans and technical systems. The Department of Defense incorporates HSI evaluations into defense acquisition to improve system performance and reduce lifecycle costs. During operational test and evaluation, HSI evaluations characterize how a system’s operational performance is affected by its users. The goal of this course is to provide the theoretical background and practical tools necessary to plan and evaluate HSI test plans, collect and analyze HSI data, and report on HSI results....

2024 · Adam Miller, Keyla Pagan-Rivera

Operational T&E of AI-Supported Data Integration, Fusion, and Analysis Systems

AI will play an important role in future military systems. However, large questions remain about how to test AI systems, especially in operational settings. Here, we discuss an approach for the operational test and evaluation (OT&E) of AI-supported data integration, fusion, and analysis systems. We highlight new challenges posed by AI-supported systems and we discuss new and existing OT&E methods for overcoming them. We demonstrate how to apply these OT&E methods via a notional test concept that focuses on evaluating an AI-supported data integration system in terms of its technical performance (how accurate is the AI output?...

2024 · Adam Miller, Logan Ausman, John Haman, Keyla Pagan-Rivera, Sarah Shaffer, Brian Vickers

Introduction to Design of Experiments for Testers

This training provides details regarding the use of design of experiments, from choosing proper response variables, to identifying factors that could affect such responses, to determining the amount of data necessary to collect. The training also explains the benefits of using a Design of Experiments approach to testing and provides an overview of commonly used designs (e.g., factorial, optimal, and space-filling). The briefing illustrates the concepts discussed using several case studies....

2023 · Breeana Anderson, Rebecca Medlin, John Haman, Kelly Avery, Keyla Pagan-Rivera

Introduction to Bayesian Analysis

As operational testing becomes increasingly integrated and research questions become more difficult to answer, IDA’s Test Science team has found Bayesian models to be powerful data analysis methods. Analysts and decision-makers should understand the differences between this approach and the conventional way of analyzing data. It is also important to recognize when an analysis could benefit from the inclusion of prior information—what we already know about a system’s performance—and to understand the proper way to incorporate that information....

2021 · John Haman, Keyla Pagan-Rivera, Rebecca Medlin, Heather Wojton

Why are Statistical Engineers Needed for Test & Evaluation?

The Department of Defense (DoD) develops and acquires some of the world’s most advanced and sophisticated systems. As new technologies emerge and are incorporated into systems, OSD/DOT&E faces the challenge of ensuring that these systems undergo adequate and efficient test and evaluation (T&E) prior to operational use. Statistical engineering is a collaborative, analytical approach to problem solving that integrates statistical thinking, methods, and tools with other relevant disciplines. The statistical engineering process provides better solutions to large, unstructured, real-world problems and supports rigorous decision-making....

2021 · Rebecca Medlin, Keyla Pagan-Rivera, Monica Ahrens

A Review of Sequential Analysis

Sequential analysis concerns statistical evaluation in situations in which the number, pattern, or composition of the data is not determined at the start of the investigation, but instead depends upon the information acquired throughout the course of the investigation. Expanding the use of sequential analysis has the potential to save resources and reduce test time (National Research Council, 1998). This paper summarizes the literature on sequential analysis and offers fundamental information for providing recommendations for its use in DoD test and evaluation....

2020 · Rebecca Medlin, John Dennis, Keyla Pagan-Rivera, Leonard Wilkins, Heather Wojton

D-Optimal as an Alternative to Full Factorial Designs- a Case Study

The use of Bayesian statistics and experimental design as tools to scope testing and analyze data related to defense has increased in recent years. Planning a test using experimental design will allow testers to cover the operational space while maximizing the information obtained from each run. Understanding which factors can affect a detector’s performance can influence military tactics, techniques and procedures, and improve a commander’s situational awareness when making decisions in an operational environment....

2019 · Keyla Pagan-Rivera