Quantitative versus qualitative data analysis
Quantitative and qualitative analysis can be defined as follows:
Quantitative data: It is numerical measurements expressed in terms of numbers
Qualitative data: It is categorical measurements expressed in terms of natural language descriptions
As shown in the following figure, 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 does not include zero
Ratio: Data is continuous with logical order as well as regular interval 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 email) and/or audible and visual data (for example, digital images or sounds). In Chapter 11, Sentiment Analysis of Twitter Data, we present a sentiment analysis from Twitter data as an example of qualitative analysis.
