Abstract
Fitting models to experimental data is done by nonlinear regression routines, which vary multiple parameters like rate constants, etc. until an optimal fit is achieved. The resulting set of parameters need not be unique. Parameters often are correlated, so that the variation of one parameter can be compensated by variations of other parameters without reducing the quality of the fit. A correlation matrix helps to clarify this point. Experimental procedures, strategies for the reduction of the number of varied parameters, and global fits enhance the reliability of derived rate constants. At the end of this chapter, the reader should be able to import data from a spreadsheet, fit them to any reaction scheme and do a critical assessment of the significance of the fitted values.
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References
Croxton FE, Cowden DJ, Klein S (1968) Applied general statistics. Pitman, London, p 625
Dietrich CF (1991) Uncertainty, calibration, and probability: the statistics of scientific and industrial measurement. Inst of Physics Pub, London, p 331
Aitken AC (1936) Statistical mathematics. Oliver and Boyd, Edinburgh, p 95
Rodgers JL, Nicewander WA (1988) Thirteen ways to look at the correlation coefficient. Am Stat 42:59–66
Hofer P, Fringeli UP (1981) Acetylcholinesterase kinetics. Biophys Struct Mech 8:45–59
Krupka RM, Laidler KJ (1961) Molecular mechanisms for hydrolytic enzyme action. J Am Chem Soc 83:1445–1460
Janert PK (2009) Gnuplot in action. Understanding data with graphs. Manning Publications Co, Greenwich, CT
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© 2011 Springer-Verlag Berlin Heidelberg
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Prinz, H. (2011). Fitting the Data. In: Numerical Methods for the Life Scientist. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20820-1_8
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DOI: https://doi.org/10.1007/978-3-642-20820-1_8
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