The Altair Community is migrating to a new platform to provide a better experience for you. In preparation for the migration, the Altair Community is on read-only mode from October 28 - November 6, 2024. Technical support via cases will continue to work as is. For any urgent requests from Students/Faculty members, please submit the form linked here
data science question
MBA_Data_Miner
Member Posts: 21 Contributor II
question for experts:
if your dependent variable is something like success percentage ( calculated on two other variables total attempts and successful attempts). Success percentage is calculated as follows:
IE Success Percentage (S) = Total successful attempts (A) / Total attempts (T)
Does it make sense to exclude total successful attempts (A) as an independent variable in predictive models using S as the dependent variable? If so, why?
I am thinking it should be excluded to avoid allowing the model to "cheat" by using a variable that is not completely independent to the dependent variable.
if your dependent variable is something like success percentage ( calculated on two other variables total attempts and successful attempts). Success percentage is calculated as follows:
IE Success Percentage (S) = Total successful attempts (A) / Total attempts (T)
Does it make sense to exclude total successful attempts (A) as an independent variable in predictive models using S as the dependent variable? If so, why?
I am thinking it should be excluded to avoid allowing the model to "cheat" by using a variable that is not completely independent to the dependent variable.
0