For the purpose of analysis, data are presented as the facts and figures collected together. It is classified into two broad categories: qualitative data and quantitative data. It is not possible to measure qualitative data in terms of numbers and it is subdivided into nominal and ordinal data. Quantitative data, on the other hand, is one that contains numerical values and uses a scope. It is further classified as discrete data and continuous data.
Data that can only take on certain values are discrete data. These values do not have to be complete numbers, but they are values that are fixed. It only contains finite values, the subdivision of which is not possible. It includes only those values which are separate and can only be counted in whole numbers or integers, which means that the data can not be split into fractions or decimals.
Discrete Data Examples: The number of students in a class, the number of chocolates in a bag, the number of strings on the guitar, the number of fishes in the aquarium, etc.
Continuous data is the data that can be of any value. Over time, some continuous data can change. It may take any numeric value, within a potential value range of finite or infinite. The continuous data can be broken down into fractions and decimals, i.e. according to measurement accuracy, it can be significantly subdivided into smaller sections.
Continuous Data Examples: Measurement of height and weight of a student, Daily temperature measurement of a place, Wind speed measured daily, etc.
Height is continuous but we sometimes don't really worry too much about minor variations and club heights into a set of discrete data instead.
on the other hand, if we count large quantities of any discrete entity. We may prefer not to think of 10,00,100 and 10,00,102 as crucially different values, but instead as nearby points on an approximate continuum.
Q: Classify the Following as Discrete and Continuous Data
Ducks in a pond.
Height of a student from age 5-15.
Number of animals in Zoo.
The result of rolling a dice.
The number of books in a rack.
Ducks in a pond are discrete data because the number of ducks is a finite number.
The height of a student from age 5-15 is continuous data because the height varies continuously from age 5-15 which is not a constant for 10 years.
The number of animals in a zoo is continuous data because the number of animals varies yearly depending on the reproduction of new animals or the arrival of new animals.
The result of the rolling is a dice is 1, 2, 3, 4, 5, 6, 7, and 8. Therefore this is discrete data.
The number of books in a rack is a finite countable number. Therefore this is discrete data.
Age is a discrete data because we could be infinitely precise and use an infinite number of decimal places, rendering age continuous as a result. However, generally, we use age as a discrete variable.
1. What is the main difference between discrete and continuous data?
Discrete data is data that can only take certain values, while data that can take any value is continuous data.
2. Can we have both discrete data and continuous data from the same experiment?
If we have quantitative data, such as the correct number of questions on a test, then the data can be continuous or discrete. Finite values have discrete data.
3. How to differentiate the obtained results as discrete and continuous data?
It is easy in many cases, discrete data is preceded by “the number of”, which makes the differentiation of results easier.