In statistics, it is important to recognise the different types of data. It is because statistical methods can be done only with the help of data types. Having knowledge of different kinds of data helps you to analyse the correct method. Data are the actual pieces of information that are collected through the study. It is observed that most of the data fall under two groups namely,
- Numerical Data or Quantitative data
- Categorical Data or Qualitative Data
Categorical or Qualitative Data
The categorical data consists of categorical variables which represent the characteristics such as a person’s gender, hometown etc. Categorical measurements are expressed in terms of natural language descriptions, but not in terms of numbers. Sometimes categorical data can take numerical values, but those numbers do not have mathematical meaning. Some of the examples of the categorical data are as follows:
- Favourite sport
- School Postcode
- Travel method to school etc.
When you observe the above example, birthdate and postcode contain numbers. Even though it contains numerals, it is considered as categorical data. The easy way to determine whether the given data is categorical or numerical data is to calculate the average. If you can be able to calculate the average, then it is considered to be a numerical data. If you cannot able to calculate the average, then it is considered to be a categorical data. Like the example mentioned above, the average of birthdate and the postal code has no meaning, so it is taken as categorical data.
In general, categorical data has values and observations which can be sorted into categories or groups. The best way to represent these data is bar graphs and pie charts. Categorical data are further classified into two types namely,
- Nominal Data
- Ordinal Data
Nominal data is a type of data that are used to label the variables without providing any numerical value. It is also known as the nominal scale. Nominal data cannot be ordered and measured. But sometimes nominal data can be qualitative and quantitative. Some of the few common examples of nominal data are letters, words, symbols, gender etc.
These data are analysed with the help of the grouping method. The variables are grouped together into categories and the percentage or frequency can be calculated. It can be presented visually using the pie chart.
Ordinal data is a type of data that follows a natural order. The notable features of ordinal data are that the difference between data values cannot be determined. It is commonly encountered in surveys, questionnaires, finance and economics.
The data can be analysed using visualisation tools. It is commonly represented using a bar chart. Sometimes the data may be represented using tables in which each row in the table indicates the distinct category.