# How to interpret coefficients from a logistic regression?

I have the following probability function:

$$\text{Prob} = \frac{1}{1 + e^{-z}}$$

where

$$z = B_0 + B_1X_1 + \dots + B_nX_n.$$

My model looks like

$$\Pr(Y=1) = \frac{1}{1 + \exp\left(-[-3.92 + 0.014\times(\text{gender})]\right)}$$

I understand what the intercept (3.92) means, but I'm now sure how to interpret 0.014. Are these still log odds, odd ratios, or can I now assert that for each incremental odds change is gender, females are 0.014 more likely to win than men. Basically, how am I to interpret the 0.014?

Basically, I want to take the probability function and actually implement it in Java for a specific program that I'm writing, but I'm just not sure if I'm understanding the function correctly to implement it in Java.

Java code example:

double p = 1d / (1d + Math.pow(2.718d, -1d * (-3.92d + 0.014d * bid)));

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This might help: en.wikipedia.org/wiki/Odds_ratio#Role_in_logistic_regression –  larsmans Jan 13 '12 at 14:59
Here is a related question. There are several others as well, e.g., this one. –  cardinal Jan 13 '12 at 15:00