Chapter 3 application

Today, I browsed the rest of the paper and started to look into the data. There are many ways of data pre-processing in chapter 3 and they can be applied into the log data.

Summary

paper:

Chapter 3:

1. Individual predictors:

Centering: the predictor has a zero mean

Scaling: each value of the predictor variable is divided by its standard deviation. Scaling the data coerce the values to have a common standard deviation of one.

Removing skewness: Box-Cox transformation

After holiday, I will start to frame questions of each chapter and try to apply them into the data.