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We still need to reconcile this, but this group appears to be doing exactly what we need to do with data entry.
The data is the number of bodies in rigor mortis from two hours on: {2, 14, 31, 14, 20, 11, 7, 4, 7, 1, 1, 2}.
I'll try to show how this is a generalization of Newton's method.
We can see the weight asymptoting by week 20. It's clearly NOT appropriate to model this with an exponential, as John Alexander curiously suggests in Curve Fitting via the Criterion of Least Squares (see Figure 12, p. 23).
So the regression serves the purpose of providing parameters for a general (differential equation) model for corn seedling growth. This is an example of a structural model: we tie an empirical model into a structural model, and learn something (or incorporate something) about the nature of plant growth.
This is not "typical", in some sense, of logistic growth. For example, "carrying capacity" is the wrong terminology: and the initial value is never greater than the "carrying capacity" -- the corn seedling doesn't start out monstrous, and then shrivel to a stalk...:)
This model is appropriate if the growth in the weight of the seedling is proportional to its weight, and proportional to a substrate which is ultimately exhausted, and itself proportional to $(K-w(t))$. So "carrying capacity" in this case is sort of the maximal size of the plant that the soil can support.
Plants are notorius for having "switches", however -- at some point they switch from producing leaves to producing flowers to producing fruit.... Lots of ugly non-linearities.
[ael: by the way -- ecosystems worldwide are already suffering serious damage.... The world won't "suddenly heat up" if we reach 450 ppm -- it's heating up right now, and we're seeing bumblebees struggle with the heat, for example. They pollinate our food -- think about it....]