Computers can find good values for the model's constants
Linear models are fitted to data by selecting the values of the two parameters b0 and b1 to minimise the sum of squares of residuals.
Unfortunately the parameters b0 and b1 of a logistic model cannot be obtained with such a simple criterion. Model-fitting for proportions is based on a method called maximum likelihood that is beyond the scope of CAST.
However many statistical programs will do the appropriate calculations for you. We therefore take a 'black box' approach and show what parameter estimation gives without further justification.
The diagram below again shows the data on survival of fruit fly eggs.
Drag the two red arrows on the logistic curve to change the parameters of the curve. Try to match the curve as closely as possible to the data.
Finally, click the button Best fit to observe the 'best' values for the parameters.