Hello Michael. I concur with your paper’s arguments. I especially like the point that lack of some variables does not make the case invalid. The fact that there were some independent and depended variables used, they must have shown a correlation, providing evidence that there was racial discrimination in the payment of salaries.
The omission of some variables only makes the evidence weak but not absent it altogether. Thus, the case was valid though the probity was limited due to omission of some variables. You have pointed out that the court of appeal should have given proof that the omitted variables if included in the model could have altered the results, making the case void. I strongly agree with you on this.
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The omission of some variables may not necessarily affect the results in a regression model. The omitted variables may or may not correlate with the dependent variables and the independent variables used in the model. If they do not correlate, then they have no effect whether included or omitted in the model. Therefore, the court of appeal needed to prove that the omitted variables affect the regression model.
You also mentioned that the omission of variables might not change the model’s outcome to the extent of disproving the case as the court of appeal assumed. Even if the omitted variables correlated with those used in the model, they would lead to overestimation or underestimation of the proof that there is racial discrimination in pay, or even mask an effect that exists. This does not mean that the evidence does not exist at all. I, therefore, support your conclusion that the Supreme Court was correct to reverse the court of appeal’s decision. There existed evidence. The case was valid. Thank you.
