Monte Carlo

Logistic regression is a commonly-used method for analyzing tests with probabilistic responses in the test community, yet calculating power for these tests has historically been challenging. This difficulty prompted the development of methods based on signal-to-noise ratio (SNR) approximations over the last decade, tailored to address the intricacies of logistic regression’s binary outcomes. However, advancements and improvements in statistical software and computational power have reduced the need for such approximate methods....

In this paper we compare data from a fairly large legacy wind tunnel test campaign to smaller, statistically-motivated experimental design strategies. The comparison, using Monte Carlo sampling methodology, suggests a tremendous opportunity to reduce wind tunnel test efforts without losing test information. Suggested Citation Hill, Raymond R., Derek A. Leggio, Shay R. Capehart, and August G. Roesener. “Examining Improved Experimental Designs for Wind Tunnel Testing Using Monte Carlo Sampling Methods.” Quality and Reliability Engineering International 27, no....