# Matching Conditional Independence Assumption

#### fridolon1999

##### New Member
Hello everyone,

I am a newbie in statistics and got stuck with an exercise.
I am not sure if I am in the right thread but I didn't know where to categorize Matching into. I've got data from Berkeley 1973: "Top 6 departments by enrollment".
Can somebody explain me why the independence condition makes sense in this case? The outcome is "total percent admitted", the treatment is "gender" and X is "field of study". In my opinion the independence condition should be violated because even if field of study is given gender isn't independent with admission rate. What are your thoughts about that? Is the independence condition plausible in this case?

Thank you very much

#### hlsmith

##### Less is more. Stay pure. Stay poor.
Hint, i think you may have a simpson's paradox dataset.

#### fridolon1999

##### New Member
Hint, i think you may have a simpson's paradox dataset.
Unfortunately I have never heard about it before. What's that?

#### hlsmith

##### Less is more. Stay pure. Stay poor.
Can you define what you mean by independence condition? Independence between what or conditional on what. Different instructors may use varied terms and definitions.

#### fridolon1999

##### New Member
@hlsmith

Okay, so basically i have a dataset for major application with male and female applicants. They use gender as treatment. I need to explain why gender (the treatment) given the field of study is independent from the outcome ( Total Pct. Admitted). Outcome ⊥ Gender |Field of Study