Beyond eyeballing: Fitting models to experimental data

Arthur Christopoulos, Michael J. Lew

Research output: Chapter in Book/Report/Conference proceedingChapter (Book)Researchpeer-review

5 Citations (Scopus)

Abstract

The oldest and most commonly used tool for examining the relationship between experimental variables is the graphical display. People are very good at recognizing patterns, and can intuitively detect various modes of behavior far more easily from a graph than from a table of numbers. The process of “eyeballing the data” thus represents the experimenter’s first attempt at understanding their results and, in the past, has even formed the basis of formal quantitative conclusions. Eyeballing can sometimes be assisted by judicious application of a ruler, and often the utility of the ruler has been enhanced by linearizing data transformations. Nowadays it is more common to use a computer-based curve-fitting routine to obtain an “unbiased” analysis. In some common circumstances there is no important difference in the conclusions that would be obtained by the eye and by the computer, but there are important advantages of the more modern methods in many other circumstances. This chapter will discuss some of those methods, their advantages, and how to choose between them.

Original languageEnglish
Title of host publicationBiomedical Applications of Computer Modeling
PublisherCRC Press
Pages195-232
Number of pages38
ISBN (Electronic)9781420041873
ISBN (Print)9780849301001
Publication statusPublished - 1 Jan 2000
Externally publishedYes

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