Summary
In this chapter, we provided an overview of the fundamentals of the different kinds or types of statistical data cleansing. Then, using the R programming language, we illustrated various working examples, showing each of the best or commonly used data cleansing techniques.
We also introduced the concepts of data transformation, deductive correction, and deterministic imputation.
In the next chapter, we will dive deep into the topic of what data mining is and why it is important, and use R for the most common statistical data mining methods: dimensional reduction, frequent patterns, and sequences.
