The post is about Quantitative and Qualitative Variables. First, we need to understand the concept of data and variables. Let us start with some basics.
The word “data” is used in many contexts and is also used in ordinary conversations frequently. Data is Latin for “those that are given” (the singular form is “datum”). Data may therefore be thought of as the results of observation. In this post, we will see about quantitative and qualitative variables too.
Data are collected in many aspects of everyday life.
- Statements given to a police officer, physician, or psychologist during an interview are data.
- So are the correct and incorrect answers given by a student on a final examination.
- Almost any athletic event produces data.
- The time required by a runner to complete a marathon,
- The number of spelling errors committed by a computer operator in typing a letter.
Data are also obtained in the course of scientific inquiry:
- the positions of artifacts and fossils in an archaeological site,
- The number of interactions between two members of an animal colony during a period of observation,
- The spectral composition of light emitted by a star.
Data comprise variables. Variables are something that changes from time to time, place to place, and/or person to person. Variables may be classified into quantitative and qualitative according to the form of the characters they may have.
Quantitative and Qualitative Variables
Let us understand the major concept of Quantitative and Qualitative variables by defining these types of variables and their related examples. The examples are self-explanatory and all of the examples are from real-life problems.
A variable is called a quantitative variable when a characteristic can be expressed numerically such as age, weight, income, or several children, that is, the variables that can be quantified or measured from some measurement device/ scales (such as weighing machine, thermometer, and liquid measurement standardized container).
On the other hand, if the characteristic is non-numerical such as education, sex, eye color, quality, intelligence, poverty, satisfaction, etc. the variable is referred to as a qualitative variable. A qualitative characteristic is also called an attribute. An individual or an object with such a characteristic can be counted or enumerated after having been assigned to one of the several mutually exclusive classes or categories (or groups).
Mathematically, a quantitative variable may be classified as discrete or continuous. A discrete variable can take only a discrete set of integers or whole numbers, which are the values taken by jumps or breaks. A discrete variable represents count data such as the number of persons in a family, the number of rooms in a house, the number of deaths in an accident, the income of an individual, etc.
A variable is called a continuous variable if it can take on any value- fractional or integral––within a given interval, that is, its domain is an interval with all possible values without gaps. A continuous variable represents measurement data such as the age of a person, the height of a plant, the weight of a commodity, the temperature at a place, etc.
A variable whether countable or measurable is generally denoted by some symbol such as $X$ or $Y$ and $X_i$ or $X_j$ represents the $i$th or $j$th value of the variable. The subscript $i$ or $j$ is replaced by a number such as $1,2,3, \cdots, n$ when referred to a particular value.
Note that statistical data can be found everywhere, few examples are:
- Any financial/ economics data
- Transactional data (from stores, or banks)
- The survey, or census (of unemployment, houses, population, roads, etc)
- Medical history
- Price of product
- Production, and yields of a crop
- My history, your history is also statistical data
Read more about Statistical Data