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Linear Analysis Lab Report

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This experiment was performed to understand the process of linear least-squared analysis as well as developing the skills to use EXCEL and having the criteria for the best line of fit to ones’ graphs. Linear least-squared analysis is a statistical method to determine a line of best fit by minimizing the sum of squares created by a mathematical function. A “square” is determined by squaring the distance between a data point and the regression line. For the 1st order kinetics graph, the y-axis was for the sum of ln(A). The straight line equation came out to be y=-0.0224x-0.546 while the regression line was at a 0.99564 which was very good. For the 2nd order kinetics graph, the y-axis was for the sum of 1/A. The straight line equation came out to be y=0.0575x+1.6104 while the regression line was at a 0.97327 which was also quite good. Each data set had 9 degrees of freedom. The F-value for the first graph was 2057.16 and the 2nd graph was 327.67. Introduction: We used a set of data using least-squares procedures and decided from the evidence whether the 1st or 2nd –order kinetics was a better suited match to describe the data. Paying attention to data analysis and plots for these graphs were the most challenging. The data involves a pair of measurements of an independent variable x and a dependent variable y. In this case, our independent variable was Time(minutes) and the dependent variable was Abs(ODU). We preformed linear least-squared analyses using EXCEL in order to

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