Discriminant Analysis - Data Mining for the Masses - page 106

ORGANIZATIONAL UNDERSTANDING

Gill's objective is to examine young athletes and, based upon their performance across a number

of metrics, help them decide which sport is the most prime for their specialized success. Gill
recognizes that all of his clients possess some measure of athleticism, and that they enjoy
participating in a number of sports. Being young, athletic, and adaptive, most of his clients are
quite good at a number of sports, and he has seen over the years that some people are so naturally

gifted that they would excel in any sport they choose for specialization. Thus, he recognizes, as a
limitation of this data mining exercise, that he may not be able to use data to determine an athlete's
“best” sport. Still, he has seen metrics and evaluations work in the past, and has seen that some of
his previous athletes really were pre-disposed to a certain sport, and that they were successful as

they went on to specialize in that sport. Based on his industry experience, he has decided to go
ahead with an experiment in mining data for athletic aptitude, and has enlisted our help.

DATA UNDERSTANDING

In order to begin to formulate a plan, we sit down with Gill to review his data assets. Every athlete

that has enrolled at Gill's academy over the past several years has taken a battery test, which tested
for a number of athletic and personal traits. The battery has been administered to both boys and
girls participating in a number of different sports, but for this preliminary study we have decided
with Gill that we will look at data only for boys. Because the academy has been operating for

some time, Gill has the benefit of knowing which of his former pupils have gone on to specialize
in a single sport, and which sport it was for each of them. Working with Gill, we gather the results
of the batteries for all former clients who have gone on to specialize, Gill adds the sport each
person specialized in, and we have a data set comprised of 493 observations containing the

following attributes:



Age : This is the age in years (one decimal precision for the part of the year since the
client's last birthday) at the time that the athletic and personality trait battery test was
administered. Participants ranged in age from 13-19 years old at the time they took the
battery.

 Strength : This is the participant's strength measured through a series of weight lifting

exercises and recorded on a scale of 0-10, with 0 being limited strength and 10 being