4 Types Of Data – Nominal, Ordinal, Discrete and Continuous

 

Introduction – Importance of Data

“Data is the new oil.” Today data is everywhere in every field. Whether you are a data scientist, marketer, businessman, data analyst, researcher, or you are in any other profession, you need to play or experiment with raw or structured data. Data has become an important asset for an organization.

Now business runs on data, most of the company’s uses data for their insights to create and launch campaigns, design strategies, launch products, and services or try out different things. According to a report, today, at least 2.5 quintillion bytes of data are produced per day.

The word “Data” arises from the Latin word “Datum,” which means “something given.” This data is so important for us that it becomes important to handle and store it properly, without any error. While working on these data, it is important to know the class of data to process them and get the right results. There are two classes of data: Qualitative and Quantitative data, which are further classified into four types: nominal, ordinal, discrete, and Continuous.

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Types of Data

Qualitative or Categorical Data

Qualitative or Categorical Data is data that can’t be measured or counted in the form of numbers. These types of data are sorted by category, not by number. That’s why it is also known as Categorical Data. These data consist of audio, images, symbols, or text. The gender of a person, i.e., male, female, or others, is qualitative data.

Qualitative data tells about the perception of people. This data helps market researchers understand the customers’ tastes and then design their ideas and strategies accordingly. 

The other examples of qualitative data are :

  • What language do you speak
  • Favourite holiday destination
  • Opinion on something (agree, disagree, or neutral)
  • Colours

The Qualitative data are further classified into two parts :

Nominal Data

Nominal Data is used to label variables without any order or quantitative value. The colour of hair can be considered nominal data, as one colour can’t be compared with another colour.

The name “nominal” comes from the Latin name “nomen,” which means “name.” With the help of nominal data, we can’t do any numerical tasks or can’t give any order to sort the data. These data don’t have any meaningful order; their values are distributed to distinct categories.\

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