Originally Posted by
porciuscato
I appreciate your efforts and I don't mean to be blunt, but despite references to P values, t-statistics &etc., your method is statistically invalid. The averages you are using are not the average of what it took to get in to GS; they are the averages of people who happened to get in -- which is a very different thing.
You have completely misunderstood what I've tried to do. I'm not trying to compare $$ spend for GS qualifiers vs non-qualifiers. This would take a large sample of people who did not qualify for GS to submit data. Instead I compared new GS qualifiers vs requalifiers. Similarly I compared GS from hub cities vs non-hub cities. The parameters I compared were drawn from a convenience sample: PQD,PQM, UAPQD, 3 year PQD, BIS, CPM, PQS and others. The sample sizes were sufficiently large, and the distributions were close to normal. I also took a close look at the residuals and q-q plots. So because of this, I felt comfortable using a parametric test such as the t-test. More sophisticated modeling could be done, but for the purposes of this simple question, I didn't think it was necessary.