F value is a variance test, which is an overall test of the whole model to see if the fitted equation is meaningful.
T value is to test each independent variable (logistic regression) one by one to see if its β value β, the regression coefficient, is meaningful.
The value of t represents the significance test value of regression parameters. When its absolute value is greater than or equal to ta/2(n-k) (which represents the value obtained according to your confidence level and degree of freedom), the original hypothesis is rejected, that is, the explanatory variable X has a significant influence on the explained variable Y when other explanatory variables remain unchanged.
The value of f is the significance test of regression equation, which indicates whether the linear relationship between the explained variables and all the explained variables in the model is significant as a whole. If F & gtFa(k- 1, n-k) rejects the original hypothesis that all explanatory variables contained in the model have significant influence on the explained variables, and vice versa.