ABSTRACT
Response surface methodology (RSM) is concerned with the development of an empirical relationship between a response variable y and a set of control variables, x1, x2, . . . , xk, that represent levels of quantitative factors believed to affect the response values. Such a relationship can be approximately represented by a polynomial model, typically of the first degree or the second degree in x1, x2, . . . , xk. The model is then fitted to a data set generated by observing y at certain values of the control variables, referred to as locations, within an experimental region denoted by R. If the fitted model is determined to be an adequate representation of the response, then it can be used to
1. Determine, through hypothesis testing, significance of the factors whose levels are represented by x1, x2, . . . , xk.
