Statistics for Data Science

Preparing

In the R example, we understand that the challenge is to predict the likelihood that a passenger would have survived; we then prepare, by loading the data so that it can be reviewed and the appropriate or best variables can be identified (to be used in a learning algorithm):

The post provides the R commands to read on the  train.csv file, using the  , delimiter, including the header row as the column names, and assigning it to an R object. It also reads in the testSet.csv , and finally uses the R Head function to display the first few rows of the datasets where the reader then sees that each row has a Survived column, which is a value of 1 if the person survived, or a value of 0 if they didn't (you can see this information in the ...