# Odds vs Odds ratio in GLM function

If I estimate a model with logistic function:

glm(Yi~Xi,Di, data=data, family=binomial(link="logit") )


where Di is dummy.

The estimated coefficients are: (Intercept) =0.9, Xi=2.3, Di=-0.33

If I exponentiated the estimated coefficients returned by this regression, are these considered odds or odds ratios?

The term (Intercept) is an odds for the response Yi when Di=0 and Xi=0. Depending the encoding, the other term(s) will represent odds ratios for the response for the specific (non-zero) levels of Di compared to 0. If Xi is continuous, the odds ratio is a ratio fo odds for groups differing by 1 unit in Xi.