COMMENTARY
• Exactly what do I expect to learn from this test and how much uncertainty can I expect to face when making a decision based on it?
• How do I know that we can understand the effect of every variable in the test on the outcome? Will I be able to under- stand how the effect of one variable changes as another variable changes? If not, why don’t we think that is impor- tant to know?
• How much uncertainty is there in the conclusions you have provided? (The answer should be quantitative, not just an opinion. For example, “We think the answer is 4, but statistical analysis indi- cates the answer is between 3 and 5 with 95 percent confidence.”)
Tese questions are straightforward; any good test plan and resulting data analy- sis addresses them. Understanding the high-level statistical concepts needed to ask them and to assess answers does not require in-depth knowledge of statis- tics. Anyone can learn with a reasonable amount of training. Asking these ques- tions will encourage due diligence from those collecting data, performing analy- sis and creating information used to make decisions.
Providing appropriate answers to the ques- tions above will certainly require more statistical knowledge than asking them and recognizing an adequate answer. Will this require everyone working with data to become a statistician? Not at all, but it is necessary that those planning experiments and analyzing data have an understand- ing of design of experiments and statistical analysis and know when to call someone more knowledgeable. Just as nearly every- one needs to understand Microsoft Excel or PowerPoint at an appropriate level to do a job, nearly everyone should under- stand statistical concepts at an appropriate
If people plan an experiment by thinking of interesting things to do, without using statistical methods to create and evaluate the plan, it’s easy to unknowingly make a mistake.
level. Otherwise, we are expecting people to manage risk without the skills needed to understand and cope with the uncer- tainty that causes the risk.
Fortunately, there are already small groups in the Army, throughout DOD and in private industry that have in-depth knowledge of applying statistical methods to the development of military systems. Some have developed extensive training. We have a small but very capable base to grow from. In addition, commercial and free software tools have seen signifi- cant increases in capabilities over the last decade. Finally, while in-person training is often more effective, we have learned to work and train remotely over the past year, and training can be done more efficiently than ever. Everything is in place to make the needed improvements in our capabil- ities to plan tests, analyze data and create the information needed to best support decision-makers. We just need leaders to help us focus.
CONCLUSION Tough we have pockets of excellence, the Army has a systemic weakness in its ability to efficiently create small data and turn it into the most useful information for decision-makers. By recognizing and understanding this weakness, we create an opportunity to fundamentally change our ability to develop military systems. For every decision based on small data,
our goal must be to create the information needed using the right statistical methods.
Tis will only happen if leaders make an effort to truly understand our current weaknesses, recognize the opportunity and begin to lead the change. Our ability to maintain military superiority may depend on it. For a given amount of resources, there is a significant risk we will achieve less than those who effectively apply statis- tical methods to small data, because day in and day out, they will make better deci- sions, both small and large. It will take time to develop the capabilities we need, but all of the necessary pieces are in place to begin to improve. To maintain our posi- tion as the world’s most powerful military, we need leadership to help us get started.
For more information on application of statistical methods to planning experiments, conducting appropriate analyses and provid- ing the most useful information to decision makers, go to
www.testscience.org.
JASON MARTIN has been test design and analysis lead for 10 years at the U.S. Army Combat Capabilities Development Command Aviation & Missile Center. He has an M.S. in statistics from Texas A&M University and an MBA and a B.S. in mechanical engineering, both from Auburn University. He is Level III certified in test and evaluation and in engineering.
https://asc.ar my.mil
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