Answers:
1) 1.817008
2) Evening (4663)
3) 2562
4) Pedestrian 1.86759
5) Male
I believe a subtle difference in the numeric portion of answer (4) is due to selecting "Age of Casualty" as a numeric field; if I leave it as a V_String, I get the same answer as Brian and also those that were originally included in the problem release. I do believe selecting it as a numeric field is "more correct" than leaving it as a string factor, though: e.g. 35 and 36 are similar ages, but "35" and "36" as string factors would have no similarity. (So goes my thought process anyway - could be wrong!)
My solution, similar to the others. I'm not sure if anyone else would agree (I'm very new to Predictive analytics), but I was thinking as I did this one that it would be nice if you could take the results of the Logistic Regression and analyze them, such as being able to take all the p-values and sort/order them to be used in additional tools later on in a workflow, rather than relying on looking at the results in the browse window. Maybe there already is a way to do this, but I couldn't seem to find the right tool.
