May I know what is the minimum acceptable R square or the range of R square (0.XX) for biological wastewater treatment model ?
I am evaluating the performance of lab-scale bioreactor in treating phenol containing wastewater. While building a model based on the performance I obtained i.e., phenol removal efficiency versus the variables, I am not sure what is the acceptable range of the R square in the model. Of course, the higher the R square the better the model. However, there is an acceptable R square of model in specific field. So, I would like to know the proper range and minimum R square for the model under the aforementioned biological wastewater treatment approach. Thank you.
Hello Chingyeh, R2 alone cannot tell a good model. I recommend you look at the adjusted R2 which will correct or adjust the model with respect to the variables. Notice that if the variable does not correct significantly to the model, the adjusted R2 will reduce but the ordinary R2 will continue to increase as more predictors are incorporated into the model. Very importantly, look at the lack-of-Fit test result. If it is insignificant, then you have a good model. Still there is a last step where you have to test your model. If your model is for predictions, then look at the pred R2 which does not have to be too different from the adj R2. For a good range of adjusted R2, consider 0.8-0.99. Be careful with overfitted models.
Hello Chingyeh, R2 alone cannot tell a good model. I recommend you look at the adjusted R2 which will correct or adjust the model with respect to the variables. Notice that if the variable does not correct significantly to the model, the adjusted R2 will reduce but the ordinary R2 will continue to increase as more predictors are incorporated into the model. Very importantly, look at the lack-of-Fit test result. If it is insignificant, then you have a good model. Still there is a last step where you have to test your model. If your model is for predictions, then look at the pred R2 which does not have to be too different from the adj R2. For a good range of adjusted R2, consider 0.8-0.99. Be careful with overfitted models.
Dear Chingyeh, I agree with Dr Maurice, only that his range is higher than the acceptable. A good model R2 for general-purpose prediction is defined from 0.75 to 0.99. It is only for models that quantify flow volumes, that R2,from experience, is staked at 0.85 to be considered good.
Please follow Maurice's suggestions and I am sure you will have a safe landing
Cheers
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