Classification of data is the categorization of data for its most effective use. The process of arranging into homogenous group or classes according to some common characteristics is called classification
Data can be classified according to
1. According to nature:
According to nature, there are two kinds of data. They are
Quantitative data: Information obtained in terms of numeric values is called quantitative data. A company is producing some house hold articles. And it wants to know the number of a particular article which is being sold in a particular city. For that, it is trying to get data from the retail stores which are selling that article. The result given by those retail stores will definitely be in some numerical values. Examples: Bills, age, height so on.
Qualitative data: Information obtained from some quality characteristics.A retail store is selling some product to the people. The store wants to know whether that particular product is mostly purchased by men or women. For this purpose, it is trying to collect data from the people. The result of the above data collection will be either men or women, not in the numeric values. Examples: Gender, religion, literacy so on
2.According to source:
Primary data: Data obtained from first hand information is called primary data. If a company wants to know the opinion of the people about the product that is being sold by it, it forms a team of staff members to collect opinion directly from the people. The data which will be collected directly from the people by the team of staff members is called primary data. In other words, if a data is collected Examples: Autobiography, Field research, survey reports so on.
Secondary data: Data collected by another source. Examples: Biography, census so on.
3.According to measurement:
Discrete data: There are some datum which will always be taking some particular values not all the values. Such data is called discrete data. In other words, we can say that data which can only be taking certain values is called discrete data. Examples: Number of students in a class, corporate stalk so on.
Continuous data:Data that can take any value. Examples: length, height so on.
We had seen definition of classification of data. Now we will see more information about discrete and continuous data.
Discrete data can take on only certain distinct values.
For example number of pages in a book are discrete value.
Continuous data can take on any value in certain range.
For example length of a film role is continuous data.