upubmt jg sboepnsboepn qvsdibtf spcbcjmjuz upubm vsdibtft qvsdibtft modify it to actually not have dependency between purchases and age make that an evenly distributed chance as well see what that does to your results do you end up with very different conditional probability of being in your  and purchasing something versus the overall probability of purchasing somethingwhat does that tell you about your data and the relationship between those two different attributesgo ahead and try thatand make sure you can actually get some results from this data and understand what' going onand 'll run through my own solution to that exercise in just minute so that' conditional probabilityboth in theory and in practice you can see there' lot of little nuances to it and lot of confusing notation go back and go through this section again if you need to wrap your head around it gave you homework assignmentso go off and do that nowsee if you can actually modify my code in that ipython notebook to produce constant probability of purchase for those different age groups come back and we'll take look at how solved that problem and what my results were my assignment solution did you do your homeworki hope so let' take look at my solution to the problem of seeing how conditional probability tells us about whether there' relationship between age and purchase probability in fake dataset to remind youwhat we were trying to do was remove the dependency between age and probability of purchasing and see if we could actually reflect that in our conditional probability values here' what 've gotgspnovnqzjnqpsusboepn sboepntffe upubmt \qvsdibtft \upubm vsdibtft gps@josbohf bhf%fdbef sboepndipjdf qvsdibtf spcbcjmjuz upubmt jg sboepnsboepn qvsdibtf spcbcjmjuz upubm vsdibtft qvsdibtft