How to find the best model for my nominal variable

[#1]

Hello,

I have a nominal response variable which can have two states 1 and 0 and 6 input variables (numeric, continuous). How can I find the best model to predict my response variable? This is probably a very broad question but I would like to understand the process of getting and building the best model for my response variable. 

So some of the questions I have are the following:

1.) How do I know if I should use Partition or Fit Model?

2.) When I use Regression (Fit Model), how do I know which Macros to use? Full Factorial, Polynomial to Degree, etc.? To which degree? The higher the better?

3.) What about the personality? Should I use Nominal Logistic or Stepwise Regression?

As you can see I am a beginner in building predictive models and would like to understand the process or maybe there is guide that I can follow to build the best model for my data.

Thanks. 

[#2]

I suggest you start with some basics.  These can be self guided or live webinars:

https://www.jmp.com/en_us/events/live-webinars/getting-started-with-jmp/getting-started-with-jmp-02a...

https://www.jmp.com/en_us/events/getting-started-with-jmp/doe-intro-kit.html

There are many ways to build models.  Additive, subtractive.  Regression from an existing data set or from a designed experiment.  The models you are capable of estimating depend on how you got the data.

[#3]

In addition to @statman 's advice, you may also want to enroll in and complete the free online SAS training experience "Statistical Thinking for Industrial Problem Solving" course. All you questions are covered in great detail in that course. Here is a link to the course registration site: SAS "Statistical Thinking for Industrial Problem Solving"