I have a model in my task; one numerical 2 categorical variable. When I want to create a formula like you do here: formula1 = 'numerical ~ C(cat1) + C(cat2)' I can observe category one slightly less than 5% so I can reject null hypothesis however I see on another video they use one categorical variable to one numerical variable right? so formula2 = 'numerical ~ cat1' and I can observe that category one is 9% what exactly means in difference here when we use these two dependent variables in formula1 and formula2 and which formula we use ?
I have a model in my task; one numerical 2 categorical variable. When I want to create a formula like you do here:
formula1 = 'numerical ~ C(cat1) + C(cat2)'
I can observe category one slightly less than 5% so I can reject null hypothesis however I see on another video they use one categorical variable to one numerical variable right?
so formula2 = 'numerical ~ cat1'
and I can observe that category one is 9%
what exactly means in difference here when we use these two dependent variables in formula1 and formula2
and which formula we use ?
That was very helpful. Thanks!
You're welcome!