# want $constant, $slope, and $error coefficients for regression equation fitting this data, where the distribution line is approximated by
# Y = $constant + $slope * x + $error
# Y = Dependent Variable (eg, widgets purchased at point in time)
# $constant = Y-axis Intercept
# $slope = Slope of the regression line
# x is Independent Variable(eg, time)
# $error = error factor, should be large for random distributions, small for 
# strongly correlated distrubions
# See http://www.tufts.edu/~gdallal/slr.htm
#dummy for now -- what's the best way to do this?