# Which regression model we use if we have each independent variables are in level?

I want to predict the y variable, my Y variable is in numeric, I have more than 15 independents variables , all are in ordinal levels like (good , better, best) , ( Acidic, not acidic) so on.. So each independent variables in levels .

I have data for year 2010 to 2016 , and I want to predict for year 2017.

Any one guide me which regression model I have to use in this case ? I am thinking multiple regression analysis , is it correct way if I have independents variables in levels?

I have 2000 data observations , and response variables are 18 all are in levels.

I am using sci kit-learn , python library.

• Nothing prohibits you from using classical regression model. Just decide which of your variables is better to split into dummy and which remain ordinal. Mar 11, 2017 at 11:05
• @StudentT ,using ANOVA , can I predict my dependent variable? So I am confuse in Regression analysis Mar 11, 2017 at 11:12
• @Bogdan, oh i see, how can I do that ? to split into dummy variables and remain ordinal? any algorithm need to use? Mar 11, 2017 at 11:15
• @StudentT, Oh i see, there is any algorithm in machine learning if they gives which model is use in this data? Mar 11, 2017 at 11:17
• As you have many observation it is possible to split into dummy every variable (without risk of overfitting). Suppose you have some variables with levels (good normal bad). If coefficients something like 5 (normal) 10 (good) then you may use ordinal variable as its coefficient will be 5. But if you have something like 1 and 50 then it is no clear step so better to use dummy. You may also formalize procedure using coefficients test but according to my experience just looking at coefficients will be enough. Mar 11, 2017 at 15:47