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:<math>SS_{exp}=\sum_{i=1}^{K} n_i(\bar{Y}_{i\cdot} - \bar{Y})^2</math>
:<math>SS_{unexp}=\sum_{i=1}^{K}\sum_{j=1}^{n_{i}} \left( Y_{ij}-\bar{Y}_{i\cdot} \right)^2</math>
:<math>R^2 = \frac{SS_{exp}}{SS_{exp}+>SS_{unexp}}</math>
I then calculated forward differences, and added one to the answer, as using central differences left truncates the data. (An inspection of the data revealed that it is vastly more likely that the 'correct' answer is found at the left end of the data than the right. Also central first difference bridge the observation, which can lead to misidentification of monotonicity.) Specifically, I used:

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