Home Price Predictor


Dean De Cock. Ames, Iowa: Alternative to the Boston Housing Data as an End of Semester Regression Project. Journal of Statistical Education, 19(3), 2011.

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  • Hi, 

    What are the confounders and non confounders used in this model? Can you provide reason on why you have chosen them to be confounders/non confounders?

    • Vaishnavi K This model was exclusively learned as a predictive model. Hence, a distinction between confounders and non-confounders is a non-issue. We would only have to make that distinction if we had the objective of performing causal inference, which was not the case here. 

    • Stefan Conrady If we had to perform causal inference on this data, what should be my confounders/Non-confounders. Few examples might help. Also, would the result change when we perform causal inference on this data.

    • Vaishnavi K In this particular case, one could not simply switch to causal inference. For instance, we know this data is a subset of a much larger dataset. Thus, the assumption of "no unobserved confounders" cannot be justified at all. So, it's a bad example for causal inference, I'm afraid.

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