An algebraic method to obtain a linear equation that best represents a set of nearly linear points will be illustrated. Secondly, various functions will be used to transform nonlinear paired data to a more nearly linear transformed data set. The algebraic method of finding the best linear approximation can be applied to the transformed data. The inverse function will transform the linear function to the mathematical model that fits the original data. This industrial way of working with data provides enrichment for linear equations, functions, and inverse functions in an algebra course.

Philip R. Carlson
Mathematics Department
General College
University of Minnesota