Lesson47 Akaike Information Criterion

With the possibilities opened up by linear and multiple forms of nonlinear regression, not to mention multiple regression, etc, how is the wise researcher supposed to choose between statistical models? It would be most helpful to have an objective criterion, wrote Hirogutu Akaike, back in ca 1974 in a paper entitled "A new look at the statistical model identification". Now cited more than 20,000 times, this approach is used in a wide array of fields to choose the best fit model. It penalizes overfitting while increasing information content. Here, with an example, I show how AIC is used.

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Note: there is a mistake in the calculation of AIC; should be 42.17 for the first model and 37.86 for the second. Sorry!