A logistic regression for loan default reports a coefficient of +0.69 on has_prior_delinquency (binary).
What does this coefficient mean?
Why did you pick that answer? Two or three sentences. The act of articulating it is what builds the judgment — not the click that follows.
Logistic coefficients live on the log-odds scale: exponentiating gives the odds ratio, and e^0.69 ≈ 2.0. So a prior delinquency roughly doubles the odds of default. The change in probability depends on where the applicant started — from 10% it moves to about 18%, from 50% to about 67% — which is why "odds ratio" is the honest summary.
A coefficient of 0.69 is not a probability. Probabilities are bounded by 1; log-odds are not.
That is how a linear-probability coefficient would read. Logistic regression is linear in log-odds, not in probability.
The coefficient compares groups; it says nothing about the level of default among delinquent applicants on its own.