This study investigates the relationship between three
visual representations (two-dimensional, three-dimensional
fixed, and three-dimensional rotatable) of multidimensional
data, and the subjects' ability to make predictions based
on the data. Output of a momentum accounting system was
simulated and graphics were rendered based on that
information. An interactive computer program was developed
and used to administer the laboratory experiment and
collect the results.
Subjects made prediction decisions based on the
graphics produced for four companies. The companies were
stratified based on size (high or low) and growth patterns
(high or low). Each subject made predictions for one type
representation for each of the four companies. Because of
inconsistencies of the sample distributions for the
different representations, nonparametric analyses were used
to examine the data. The subjects using the
three-dimensional data that could be rotated were found to
provide the most accurate predictions. No differences
between the treatments were found based on the subject's
visual acuity, as measured by the Visual Vividness Imagery
Questionnaire (VVIQ). The subjects using the two-
dimensional representations were found to take the least
amount of time for their predictions.
Archiving fee received.
UMI fee received/NA.