  Angular distributions of differential cross sections from the latest CLAS
data sets \cite{bradford}, for the reaction ${\gamma}+p {\to} K^{+} +
{\Lambda}$ have been analyzed using associated Legendre polynomials. This
analysis is based upon theoretical calculations in Ref. \cite{fasano} where all
sixteen observables in kaon photoproduction can be classified into four
Legendre classes. Each observable can be described by an expansion of
associated Legendre polynomial functions. One of the questions to be addressed
is how many associated Legendre polynomials are required to describe the data.
In this preliminary analysis, we used data models with different numbers of
associated Legendre polynomials. We then compared these models by calculating
posterior probabilities of the models. We found that the CLAS data set needs no
more than four associated Legendre polynomials to describe the differential
cross section data. In addition, we also show the extracted coefficients of the
best model.
