Processing data

Overview

While statistical analysis is important and cool, you will spend the majority of time with your data in the pre-analysis stages.

Estimates are that for any real-world analysis, up to 80% of your time is spent getting the data ready to do the actual statistical model fitting. This module focuses on that 80%.

Learning Objectives

• Be familiar with the concept of data wrangling.
• Know what to do with missing data.
• Know how to handle outliers.
• Be aware of feature engineering.

Content

The module consists of the following units:

• Data processing introduction
• Data loading
• Dealing with missing data
• Dealing with outliers
• Creating new data/variables
• Merging data