CONTRASTING SLIDING POLYNOMIAL SMOOTHING AND POLYNOMIAL REGRESSION INDATA-ANALYSIS

Data processing is a necessary step in organizing and summarizing nume rical results of experimentation. Various methods have been proposed a nd utilized. Results of agricultural research as well as other natural resource research may depend upon the methods of data analysis and mo dels used as well as upon the experimental data themselves. Two types of data analysis have been contrasted in this article: sliding polynom ial smoothing and polynomial regression. Smoothing is shown to be supe rior in adherence to the data, in subduing polynomial bounce, and in m aintenance of required symmetry. It is shown that adequacy of data ana lysis cannot always be measured by goodness-of-fit.