- Thread starter eunkum1
- Start date

Adjusted R-square doesn't have the same interpretation as R-square itself - you can't talk about it in terms of % of variation explained by the model.

*sigh* another assumption I learned in class wrong....

Effectively if adjusted R square is below 0 it has no explanatory value.

We know that the variation in genes explains the variation in length to a great deal, lets say 95 percent. The rest is explained by various environmental factors. Now, the marginal effect of environmental factors on length is very low according to R2 and adj-R2, but you can still influence the length to a great deal by altering envionmental factors. For example, you can cut off your legs and voila, you're only 84 centimeters tall. Thus the variation in environmental factors does not affect the variation of length to a great deal (since not so many cut off their legs), but environmental factors can explain length to a great deal.

Please let me now if my logic contains any flaws =)

You have to consider what the purpose of a statistic is in using it. Rsquare looks at what explains variance in actual reality. Not the theoretical impact on variation something could have, if it does not occur often enough in fact to matter.