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(1) Fitting data by hand to nonlinear models was much more challenging to most students and practitioners.

Uncertainties in these values were sometimes determined by manipulating these lines through a range of “fits” that was tacitly judged to reflect a reasonable deviation in the fit. Moreover, it was often considered acceptable practice to “eye ball” a straight line through hand-plotted data points for analysis according to a linear model. Before the advent of these computing resources, when slide rules and mechanical calculators were the means available to most students and researchers, it was necessary to transform data into a linearized form to obtain the slope and intercept values for further analysis.

Standards and expectations of the rigor and sophistication of data analysis have increased dramatically as a result of the increasing availability and power of computing resources, from centralized mainframe resources, to dedicated laboratory computers, to hand-held and desktop or laptop computers, and to smart phones. Other example topics are chemical and enzyme kinetics, vapor pressure, and quantum chemistry computational results. The use of the Regression Analysis tool is illustrated with several examples including the unweighted and weighted analysis of the nonlinear and linearized forms an exponential decay and an example of the use of the covariance term in a propagation of errors calculation.

SDAT includes the following functionalities: Descriptive Statistics, Integrate, Differentiate, Smooth, Spline, Plot, and Regression Analysis. It also supports weighted regression analysis. This tool, which can accommodate up to seven fitting parameters, provides the standard deviation of regression of the fit, the standard uncertainties of the fitting parameters, and the covariance matrix. A particularly useful feature of SDAT is its ability to perform rigorous regression analysis using both standard and user-defined model functions. It has been designed for student use in manipulating and analyzing data encountered in the physical and biological sciences, from first-year courses, to the graduate level, and in research. SDAT uses the familiar Excel environment to carry out most of the analytical tasks used in data analysis. Scientific Data Analysis Toolkit (SDAT) is a rigorous, versatile, and user-friendly data analysis add-in application for Microsoft Excel for Windows (PC).