How to write down a logistic regression formula for continuous and categorical variables? I have a logistic regression with five explanatory variables (x) and Y is binary. 
I will present a small work tomorrow on a powerpoint and wondering what the neatest way is to write my logistic regression?
my variables:
x_1: categorical, with the categories: teachers, biomathematics, economics and mathematics. Mathematics is the reference variable.
x_2:age, continuous
x_3: gender(Woman=1, man=0)
x_4:preparatory course: (Yes=1, No=0)
x_5: calendar, continuous
I have received a total brain release and can not figure out how to write the nicely on the presentation. 
Could someone write down the formula to me?
 A: The formalism used to write models in R can be quite handy, in this case with factor variables explicitly noted:
Y ~ age + calendar + factor(teacher) + factor(gender) + factor(prep_course)
You could expand to indicate more specifically that this is a logistic regression, and I suppose to indicate the reference levels of the factor variables (although that probably isn't so important for your presentation).
A: If you're going to explain the model as percent change of odds, I would use the same equation.
$$
\frac{\pi(x)}{1-\pi(x)} = e^{\alpha + \beta_1teacher + \beta_2biomathematics + \beta_3economics + \beta_4age + \beta_5woman + \beta_6prep + \beta_7calendar}
$$
But given 5 dummy variables, I agree that this might be cumbersome for a powerpoint slide. Have you considered using an equation for just the continuous effects and creating a separate table for all the categorical effects? 
$$
\frac{\pi(x)}{1-\pi(x)} = \gamma e^{\beta_4age+ \beta_7calendar}
$$
                  mathematics teachers biomathematics economics
man    no prep     gamma_1
man    prep        gamma_2
woman  no prep     gamma_3
woman  prep        

Then fill out the entire table with the evaluated coefficients as percent increase over the equation.
$$
\begin{align}
\gamma_1 &= 100(e^\alpha-1)\%\\
\gamma_2 &= 100(e^{\alpha + \beta_6}-1)\%\\
\gamma_3 &= 100(e^{\alpha + \beta_5 + \beta_6}-1)\%\\\
...
\end{align}
$$
