So we have seen how to run a logistic regression with single predictor and how to interpret it is that
we get now we'll be running.
So just integration with multiple predictors.
It isn't exactly same as what we did with single predictor only defenses.
The inverse of this price variable will be using all other variables to denote that we want all variables
except the independent except be dependent variable.
We can user dort.
So instead of just place, we'll be using all independent variables and the dependent variable is same
method.
So we need to link both of these statements.
And on them.
So here is the result.
You can see the list of variables is on the left.
These are all the variables that we had in our dataset.
On the right, we have beta values.
This intercept is beta zero, which is minus two point one three.
Price has a end of minus zero point two seven and so on.
The second column is standard error.
Third is.
Lou.
We are not really concerned about standard error and devalues in straight away look at the P value to
identify which all variables are significantly impacting our response variable.
So using just those two lines, we can pretty model and see the estimate coefficient.