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Types of Data

Types of Data – Qualitative Data and Quantitative Data | Business Statistics

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Types of Data | Qualitative Data and Quantitative Data | Business Statistics

 

Types of Data

Statistics is based on statistical data. Depending on what we are interested in, the data may pertain to a phenomenon, a situation under study, or an activity that is of interest to us. A measurement, a count or an observation is what they represent. Therefore, statistical data refers to those aspects of a problem situation that can be measured, quantified, counted, or classified. A variable is the result of the interaction of an object with data, or the activity of generating it. Variables are also those that show a degree of variability among consecutive measurements.

Statistics classifies data into two broad categories: Quantitative and Qualitative. It identifies characteristics that can be measured and categorizes them accordingly. There are definite units of measurement that can be used to quantify quantitative data. The units of measurement are characteristics whose successive measurements yield quantifiable observations.

Quantitative Data

Quantitative data can be further classified as continuous and discrete data depending on the nature of the variable observed for measurement. Obviously, a variable may be a continuous variable or a discrete variable.

(i) Continuous Data

Continuous data consist of numerical values of a continuous variable. Continuous variables can take any value between any two points on a line segment, thus representing an interval of values. Despite being close to each other, the values are distinguishable. Continuous variables include weight, length, height, thickness, velocity, temperature, tensile strength, etc. Thus, continuous data is data that records these characteristics and others similar to them. Continuous variables require a finer unit of measurement than discrete variables. It is the finest when it comes to the ability to perform measurements to the greatest degree of accuracy.

(ii) Discrete Data

Discrete data are the values assumed by discrete variables. There are two types of discrete variables: count variables and categorical variables. This type of information basically consists of counts. A measurement derived from counting, such as the number of items that possess or do not possess a certain characteristic. A discrete data set would include the number of customers in an everyday department store, the number of incoming flights at a nearby airport, and the number of items that are defective in a consignment that has been received for sale.

Qualitative Data

Qualitative data refer to the qualitative characteristics of a subject or an object. Qualitative characteristics are defined and described in terms of a discrete number of items containing a specific attribute and hence are qualitative in nature. They can be further divided into nominal and rank variables.

i) Nominal Data

Nominal data result from categorizing items or units into two or more groups based on certain quality characteristics. All categories of students according to gender (male or female), workers according to skill (skilled, semi-skilled, and unskilled), and employees according to educational level (matriculates, undergraduates, and postgraduates) result in nominal data. Whatever the basis for classification, it is always possible to assign each item to a particular class and sum the items within that class. Nominal data thus obtained are known as count data.

(ii) Rank Data

Rank data are the results of assigning ranks to specified order by the integers 1, 2, 3, …, n. Ranks can be assigned according to the level of performance in a test, a contest, a competition, an interview, or a show. As a result of their performance in an interview, the candidates may be assigned ranks ranging from 1 to n. In this instance, the ranks correspond to continuous values involving performance as a quality characteristic.

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