Prediction of batch heat transfer coefficients for pseudoplastic fluids ...

43
find the effects of one or two other groups (30,32).
These methods leave much to be desired because there
is much scatter in most of the experli.~ental
data and fitting
a straight line "by eyell is an almost hopeless task.
Due
to the scatter of the data the slope of the line drat-ill to
represent the data :t;s subject to hwaan error and choice.
This is evidenced by the large number of Itrecalculations[!
reported in the literature.
A more scientific approach to the task of correlating
the experimental data is to use a rtleast squares ll method
of mathematically fitting a straight line through a set of
data points (49,]82).
For the many variables such as obtained
in a heat transfer study a multiple variable regression
analysis is described by Levenspiel et ale (K5) and Volk
(198). This method eliminates the proble:m of strict experimental
control because it provides an objective and
reliable estimate of the true values of the exponents.