Not all data are the same
Researchers deﬁne data in different ways. For example, data are categorical if the values can be sorted into non-overlapping categories (eg by blood type, species or sex). Every value should belong to only one category, and it should be clear which one it belongs to.
Categorical data are also known as ‘nominal data’, or ‘frequencies’, as the research looks to ﬁnd out how frequently data fall into each category. Ordinal data, by contrast, can be ranked or have some sort of rating scale. Ordinal data often come from surveys and questionnaires.
Data can also be deﬁned as discrete or continuous. Data are discrete, or discontinuous, if they can take only isolated values. Continuous data can take on any value and are limited only by how accurate your measurements are. So, while foot length is continuous, shoe size is discrete because you can’t be a size 7.234434 – you have to be a 7 or a 7.5.