# interpretation of GLM output

I want to get verified if I can say like this.

here is the GLM output:

glm(formula = purchase ~ PC1 + month + weekday + job,
family = binomial(link = "logit"), data = data_train)

Deviance Residuals:
Min      1Q  Median     3Q    Max
-2.4295 -0.8625 -0.5331 0.8478 2.1372

Coefficients:
Estimate Std. Error z value  Pr(>|z|)
(Intercept) -0.107928  0.117437  -0.919  0.358083
PC1          0.644329  0.023459  27.466  < 2e-16  ***
monthaug    -0.029188  0.117221  -0.249  0.803357
monthdec     1.120358  0.474668   2.360  0.018260 *
monthjul     0.469336  0.121083   3.876  0.000106 ***
monthjun     0.483871  0.126402   3.828  0.000129 ***
monthmar     0.873300  0.204628   4.268  1.97e-05 ***


Let's say if the base level is monthjan (i.e. January). Can you please verify if this interpretation for the selected feature is fine?

Given that we change from January (i.e. base level) to March, the predicted odds (i.e. $$\frac{\hat{\mu}}{1-\hat{\mu}}$$) will increase by 239% if all the other variables stay the same.

Also, "the predicted" is needed in the sentence?