
One of Boehm's original motivation for creating COCOMO  was to decrease
the number of errors managers make when estimation software projects.
At the early software development stage such as
investigation and inception phase, the characteristics of software
system are unknown; the nature of the processes, team, and personnel
experiences are still unclear; the degree of understanding
architecture, requirements, and constraints are low. When the
software project goes into further development phase, more knowledge
of the project is available so  predictions better approximate the 
actual cost.

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Strangely, despite the original  motivation for COCOMO, very little has been reported on
the variance on COCOMO's estimates.  Numerous
COCOMO calibration studies have been reported~\cite{boehm00b}
and, with only one exception, these studies just report mean
results over the  training data.
The one exception was Chulani et.al.'s 
report where the min, mean, and max values seen in 15 {\em
holdout studies}\footnote{Where $\frac{1}{3}$ of the available data is
selected at random for testing, while the remaining data is used for
training.}~\cite{chulani99}. Chulani did not report the standard
deviation in their holdout experiments and without that information
since they repeated their holdouts only 15 times (a number too small
to collect accurate information about standard deviations).
Hence, in the sequel, we report variances across a large number (30) of
hold-outs studies.
