11.5 HOW TO PERFORM MULTIPLE REGRESSION MODELING USING R
Load the clothing_sales_training and clothing_sales_test data sets as sales_train and sales_test, respectively. Next, make sure the binary variables are factors in both data sets.
sales_train$CC <‐ as.factor(sales_train$CC)
sales_train$Web <‐ as.factor(sales_train$Web)
sales_test$CC <‐ as.factor(sales_test$CC)
sales_test$Web <‐ as.factor(sales_test$Web)
Now, run the full model for the training data set.
model01 <‐ lm(formula = Sales.per.Visit ~ Days + Web + CC, data = sales_train)
Notice the two pieces of input that are required: formula and data. The formula takes the same Target ~ Predictors form we have seen before. The data = sales_train input specifies the data set that our variables come from. We save the results of the regression modeling under the name model01. To view a summary of the model results, run the summary() command on model01.
summary(model01)
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