Which Regression Model Is More Realistic: Linear or Logarithmic?

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there are two regreesion model Eviews output... which one is more realistic?

model 1:
wagehat = 116.9916 + 8.303*IQ
model 2:
logwagehat = 5.88 + 0.0088*IQ

both of them use same samples...

do i need to know futher statistic information to judge which one is more realistic? such as Rsquare or some thing?
 
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wow007051 said:
there are two regreesion model Eviews output... which one is more realistic?

model 1:
wagehat = 116.9916 + 8.303*IQ
model 2:
logwagehat = 5.88 + 0.0088*IQ

both of them use same samples...

do i need to know futher statistic information to judge which one is more realistic? such as Rsquare or some thing?

This question is impossible to answer without knowing the actual data. You can find more info in http://en.wikipedia.org/wiki/Regression_model_validation . Click on the external link "How can I tell if a model fits my data" to see a lot more on this topic.

RGV
 
There are two things I don't understand about this problem. First, when finding the nth root of a number, there should in theory be n solutions. However, the formula produces n+1 roots. Here is how. The first root is simply ##\left(r\right)^{\left(\frac{1}{n}\right)}##. Then you multiply this first root by n additional expressions given by the formula, as you go through k=0,1,...n-1. So you end up with n+1 roots, which cannot be correct. Let me illustrate what I mean. For this...
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