Quantitative data are numerical measurements expressed in terms of numbers.
Qualitative data are categorical measurements expressed in terms of natural language descriptions.
As is shown in the following image, we can observe the differences between quantitative and qualitative analysis:
Quantitative analytics involves analysis of numerical data. The type of the analysis will depend on the level of measurement. There are four kinds of measurements:
Nominal data has no logical order and is used as classification data.
Ordinal data has a logical order and differences between values are not constant.
Interval data is continuous and depends on logical order. The data has standardized differences between values, but do not include zero.
Ratio data is continuous with logical order as well as regular intervals differences between values and may include zero.
Qualitative analysis can explore the complexity and meaning of social phenomena. Data for qualitative study may include written texts (for example, documents or e-mail) and/or audible and visual data (digital images or sounds). In Chapter 11, Working with Twitter Data, we will present a sentiment analysis from Twitter data as an example of qualitative analysis.