Professional oboe players almost always have to make their own reeds,
which involves a time-consuming process often fraught with wasted effo
rt and discarded results. About one fourth of the total time spent on
a reed involves getting it to a stage where it can be tried out on the
oboe. Regression analysis was used to aid in making predictions about
the ultimate quality of a finished reed based on data available at th
e initial try-out. The inputs to the regression model consist of sever
al different characteristics of the cane used in making the reeds, and
an assessment of the reed in its early stages through this initial tr
y-out on the oboe. The goal to be able to decide whether or not to con
tinue to work on the reed past this stage, based on the predictions of
the regression. Thus far, the outcomes predicted by the regression ha
ve coincided reasonably closely with the actual outcomes in trials. Se
veral regression models were tried, ranging from pure linear to curvil
inear models that include interaction terms and/or squared terms. A pa
rticular curvilinear model was deemed the most appropriate.