basprotection.blogg.se - Graphpad prism 8 curve fitting guide

In addition, a protocol has been implemented with the sum of squared errors and the Akaike’s Information Criterion methods in order to evaluate different curve fit models to best represent the data.

This technical note discusses the different linear and non-linear regression models available in SoftMax Pro 7. These ensure that the plotted curve is as close as possible to the curve that expresses the concentration versus response relationship by adjusting the curve fit parameters of the chosen model to best fit the data. SoftMax® Pro 7 Software offers 21 different curve fit options, including the four parameter logistic (4P) and five parameter logistic (5P) nonlinear regression models. Therefore, the goal of curve fitting is to find the parameter values that most closely match the data, or in other words, the best mathematical equation that represents the empirical data. The curve fit of choice should represent the most accurate relationship between two known variables: x and y.

High-Content Screening with AgileOptix TechnologyĬhoosing the correct curve fit model is crucial when determining important characteristics of data such as the rate of change, upper and lower asymptotes of the curve, or the EC 50/IC 50 values.

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