Confirming the dependent variable / outcome in logistic regression I'm running logistic regressions in Python using statsmodels logit.  My dependent variable is binary, 0 or 1.
How do I know whether the regression is modeling an outcome of 1 or an outcome of 0 for the dependent variable? (And, therefore, whether the coefficients correspond to an outcome of 1 or 0?)
For example, one of the parameters, age, has a positive coefficient of 0.03.  How do I know whether age is positively correlated with outcome == 1, or positively correlated with outcome == 0?  ​

Logistic regression predicts $P(1)$, and we get $P(0)$ via $1-P(1)$. Remember that the GLM deals with a binomial response variable that models the probability of getting a "success", defined as $1$ in the usual way we define the binomial PMF.
Therefore, a coefficient of $0.03$ means that, for every one-unit increase in the corresponding variable, expect an increase of $0.03$ in the log-odds of $1$.
(Always keep in mind that logistic regression is predicting a log-odds (or a probability, depending how you elect to look at it), not a discrete outcome. Predicting discrete outcomes is surprisingly problematic.)
