Andrzej Wierzbicki
Linear Least Squares Regression JCE
Sidney H. Young, University of South Alabama
Andrzej Wierzbicki, University of South Alabama
Linear least-squares regression is the workhorse mathematical tool of the physical chemistry laboratory. This Mathcad worksheet and its accompanying data files demonstrate various implicit and explicit methods for determination of slope and intercept of a regressed line.
Non-Linear Least Squares Regression JCE
Sidney H. Young, University of South Alabama
Andrzej Wierzbicki, University of South Alabama
Nonlinear least-squares regression is often required in the physical chemistry laboratory. It is especially important for fitting functions that cannot be linearized. This template demonstrates various implicit and explicit methods for determining the parameters of the regressed curve obtained by nonlinear curve-fitting.