Hi Dale - Thanks so much for responding. As I responded to ih a few minutes ago, while I understand what an inverse prediction is and what it does, I am uncertain how to read the meaning of the results I am getting as they do not seem to align with my raw data (which means I am misinterpreting something). I just ran the inverse prediction again for this JMP Discussion Group response and, to demonstrate my issue, this time I am using "above 235" (i.e. if ecoli > 235, my "above 235" column equals 1, otherwise it equals 0) which is a nominal dependent variable.... vs ....turbidity (continuous independent variable). I then ran the inverse prediction with a 95% confidence level and a 90% probability (one tail, upper 95%). It produced a value for turbidity of 5.3. That is, if turbidity is > 5.3, I am 95% confident that 90% of my ecolis will be above 235. However, my raw data suggests that this is wildly in error as only 71% of the ecolis (106 of 149) are above 235 when turbidity is > 5.3. I would have thought that close to 90% of the ecoli instances (~134 of 149) would have been above 235 when turbidity > 5.3. Am I missing something?