Simple logistic regression is used when there’s a nominal variable with two values (yes/no, male/female, etc) and one measurement variable. The measurement variable (x) is the independent variable and the nominal variable is the dependent variable (y), that is, the measurement variable affects the nominal variable.
Simple logistic regression finds the equation which best predicts the value of the nominal value for each of the measurement variable’s value. Logistic regression doesn’t measure the nominal variable directly, it instead estimates the probability if obtaining a particular value of y.
You can read more about simple logistic regression here.
Source: ‘Handbook of Biological Statistics’ by John H. McDonald