As we know we can use linear models for numeric dataset(independent variables are numerical only), but what type model is applicable here when I have numeric + categorical dataset(independent variables are combination of numeric and categorical).
for example I have two datasets
1.numeric dataset 2.numeric dataset + categorical dataset
1.numeric dataset (Prediction of price of home) Independent variables x1 = numbers of bedrooms x2 = size of home in sq. feet dependent variable x3 = price of home here dependent variable is numerical independent variable is with numerical values 2.numeric dataset + categorical dataset(prediction of web visits) Independent variables x1 = search time x2 = search query x3 = browser x4 = country dependent variable x3 = visits here dependent variable is numerical independent variable is with combination of numerical and categorical values
I assume here that for dataset 1 linear model with lm() is applicable, but its not possible for second dataset. can any one suggest best technique for dataset 2 to be implemented with model for prediction.