Data can be understood as quantitative information on a specific characteristic. The characteristic may be qualitative or quantitative, but for the purposes of statistical analysis, the qualitative characteristic is transformed into the quantitative one, providing numerical data of that characteristic. So, the quantitative characteristic known as variable . Here in this article, we will talk about the discrete and continuous variable.
|Sense||The discrete variable refers to the variable that assumes a finite number of isolated values.||The continuous variable alludes to the variable a which takes on an infinite number of different values.|
|Specified number range||To complete||incomplete|
|Values||Values are obtained by counting.||The values are obtained by measuring.|
|takes||Distinct or separate values.||Any value between the two values.|
|Represented by||Isolated points||Connected points|
Definition of discrete variable
A discrete variable is a type of statistical variable that can take only a fixed number of distinct values and lacks an intrinsic order.
Also known as categorical variable, because it has separate and invisible categories. However, no value can exist between two categories, that is, it does not reach all values within the limits of the variable. So, the number of allowed values it can assume is finite or infinitely countable. So if you can count the set of elements, then the variable considered discrete.
Definition of continuous variable
Continuous variable, as the name suggests, a random variable that takes on all possible values in a continuum. In a nutshell, it can take any value within the specified range. So, if a variable can take an infinite and uncountable set of values, the variable is indicated as a continuous variable.
A continuous variable is what is defined on a range of values, in the sense that it can assume any value between the minimum and maximum value. It can be understood as the function for the interval and for each function, the interval for the variable can vary.
Key differences between discrete and continuous variables
The difference between discrete variable and continuous variable can be clearly traced for the following reasons:
- The statistical variable which assumes a finite set of data and a countable number of values, is therefore called a discrete variable. On the contrary, the quantitative variable that assumes an infinite set of data and an innumerable number of values known as a continuous variable.
- For the classification not superimposed or otherwise known as mutually inclusive, in which both class limits are included, applicable for the discrete variable. On the contrary, for the overlapping or for the classification that are mutually exclusive, in which the upper limit of the excluded class, applicable for a continuous variable.
- In the discrete variable, the range of the specified full number, which is not the case for a continuous variable.
- Discrete variables are variables, in which values can be obtained by counting. On the other hand, continuous variables are random variables that measure something.
- The discrete variable takes on independent values while the continuous variable takes on any value in a given range or continuum.
- A discrete variable can be represented graphically by isolated points. Unlike, a continuous variable that can be indicated on the graph with the help of connected points.
- Number of printing errors in a book.
- Number of traffic accidents in New Delhi.
- Number of siblings of an individual.
- Height of a person
- Age of a person
- Profit earned by the company.
In general, both the discrete and continuous variables can be qualitative and quantitative. However, these two statistical terms are diametrically opposed to each other in the sense that the discrete variable is the variable with the well-defined number of allowed values while a variable continues a variable that can contain all possible values between two numbers.