Dear colleagues,
Building on the excellent points raised about uncertainty and communication, I'd like to share a practical experience from a structural analysis course I taught, where students explored multiple approaches to solving the same problem.
One case involved applying the moment distribution method in Excel. A conventional, conservative use of this method often yields a safe result, but it can obscure subtle shifts in structural behavior. By deliberately increasing the internal precision (e.g., retaining more decimal places through iterative cycles), we uncovered outcomes that were not only more accurate; but also revealed opportunities for more efficient design results, comparable to those produced by advanced analysis software.
This level of precision is not a computational artifact; it's a gateway to the model's full predictive power. The key takeaway, which echoes your insights, is that we must be masters of our tools. We need to discern when internal precision is essential for rigorous analysis, and just as importantly, when and how to round results for effective communication with clients, who often care more about scale than decimal detail.
Thank you for this thoughtful and engaging discussion.
Warm regards,
Abubakr Elfatih Ahmed Gameil
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Abubakr Gameil, R. ENG, M. ASCE®️, SEI Member
Chairman & Director General
Almanassa Engineering International Co. Ltd
Khartoum, Sudan
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Original Message:
Sent: 09-03-2025 09:31 AM
From: Christopher Seigel
Subject: Significant Figures Aren't Significant
One thing I have found that is important to impart to junior staff is the concept of uncertainty. Often in reports, I encourage them to round numbers to a certain extent. For example, instead of telling a client that a given model predicts a reduction of 81.52 MG of flow, state that is it "on the order of 80 MG" or something similar. This is an area where I feel I could continue to improve myself, in terms of understanding how much to round based on the type of modeling performed.
I also recognize that there are jobs in this field where high degrees of precision are actually required, but it is important to understand when that precision is real and when it is an artifact of the calculations you have performed.
Does anyone else have other examples of either ways they handle significant figures in communication results to others? Or perhaps any useful terminology they employ in these forms of communication?
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Christopher Seigel P.E., M.ASCE
Civil Engineer
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