Representing Quantitative Data

Abstract

In Chapter 2, we learned about four basic analytical data types. Quantitative data – interval and ratio – are among the most common types and are often the most problematic due to the great variety of measurement units and size ranges. Units vary by knowledge domain, usage conventions, national and historical origins, and formal or organizational standards. Sizes range from the infinitesimal to the cosmic in fields like economics, computer science, quantum physics, and astronomy. Ensuring good quantitative data requires selection and recording of appropriate units and defining them in the data dictionary for the dataset and avoiding any unit labels in the data itself. In this chapter, we review how common quantities and measurements are expressed and caution how mixing unit types can cause time-consuming data cleanup tasks.