100 LearnersLast updated on June 4th, 2025
Discrete Data
Data is classified into different types based on how it is represented. Discrete data is an important type of data that consists of distinct and separate values. It is typically obtained by counting and cannot be broken down into smaller fractions. In this topic, we are going to learn about discrete data and how it is different from continuous data.
What is discrete data?
Data that consists of distinct and separate countable values is called discrete data. It is the data that represents only whole numbers and not decimals or fractional values. We typically obtain discrete data by counting rather than measuring.
Let us use an example, imagine counting the number of students in a classroom. There can only be 21, 22, or 30 students, but we cannot have 21.5 students. This is what we call discrete data. Data that can only be obtained by counting the number of values and is distinct is called discrete data.
Difference Between Discrete and Continuous Data
There are many types of data that we know of, but two of the main or important data types are discrete and continuous. The differences discrete and continuous data are mentioned below:
|
Discrete Data |
Continuous Data |
|
Data that consists of distinct values that can be obtained only by counting. |
Data that can take values within a given range of data and can be measured. |
|
Discrete data can only contain whole numbers |
Continuous values can contain decimals and fractions as well. |
|
We can only gather data by counting and it can't be measured |
Continuous data is measured such as length, time, height, etc |
|
Usually, data is represented in bar charts |
Here, any value can be selected within a range. |
|
Number of cars in a parking lot (can only be whole numbers) |
Height of students (can be decimals as the height can be 5.8 feet) |
How to analyze discrete data?
Discrete data can be gathered by counting the number of values. To analyze the discrete data, we need to find patterns of trends and insights. A few of the steps are as follows:
Step 1: First, we collect and organize the discrete data clearly in a table or list.
Step 2: Next, we choose a graph or a measure (mean, median, mode) to calculate the data collected.
Step 3: Look for any patterns or trends.
Step 4: Answer any questions that are based on the data analysis gathered.
Graphical representation of Discrete data
To represent discrete data graphically, the following types of graphs can be used:
- Graphs (bar charts, pie charts, histograms, etc.)
- Frequency Table
- Line Plot (number line)
Graphs are one of the most suitable ways to represent discrete data. The reason is graphs can present finite values clearly, such as in bar graphs or pie charts.
Frequency tables represent discrete values through tally marks and the frequency of each variable.
On number lines, each value is marked with the variable.
Real-life applications of Discrete Data
There are many uses for discrete data in our day-to-day life. Let us now see the various fields and applications we use in discrete data:
- Business and Marketing: We use discrete data in business and marketing to calculate the number of purchases made by a customer in a month. To check the page views, clicks on ads, or number of unique visitors. We also use it in survey responses, inventory management and loyalty programs.
- Healthcare and Medicine: Discrete data is widely used in medicine and healthcare to calculate the patient counts, disease cases, to calculate the medication dosages, to check blood pressure readings and birth and death rates of different types of patients.
- Education and Academia: The concept of discrete data is used in education and data. We use it to check the student attendance, to check the marks obtained in an exam, to check the number of courses enrolled in a semester. Furthermore, we also use it to see the number of books issued to a student and to count the number of graduating students each year.
Common Mistakes and How to Avoid Them in Discrete Data
Students tend to make mistakes when they solve problems related to discrete data. Let us now see the common mistakes they make and the solutions to avoid them:
Mistake 1
Using a Continuous Scale for Discrete Data:
Students should remember to use a bar graph or a dot plot, in which the bars of the bar graph are not touching each other.
Solved examples of Discrete Data
Problem 1
Find the mean of the data set: 3, 7, 4, 6, 5.
The mean of the data set is 5.
Explanation
Sum the values:
3 + 7 + 4 + 6 + 5 = 25
Count the number of values:
There are 5 numbers.
Divide the sum by the count:
Mean = 25/5 = 5
Problem 2
Determine the median of the data set: 8, 3, 5, 9, 6, 7, 4.
The median of the data set is 6
Explanation
Sort the data in ascending order:
3, 4, 5, 6, 7, 8, 9
Identify the middle value:
With the data containing 7 values, the 4th value is the median, which is 6.
Problem 3
Find the mode of the data set: 2, 4, 4, 6, 7, 4, 8, 9.
The mode of the data set is 4
Explanation
Count the frequency of each number:
2 appears 1 time
4 appears 3 times
6 appears 1 time
7 appears 1 time
8 appears 1 time
9 appears 1 time
Determine the most frequent value:
The value 4 appears most frequently.
Problem 4
What is the range of the data set: 10, 5, 15, 20, 8.
The range of the data set is 15
Explanation
Identify the minimum and maximum values:
Minimum = 5 and Maximum = 20.
To calculate the range, subtract the minimum from the maximum:
Range = 20 – 5 = 15.
Problem 5
A student recorded the number of books read in a month: 2, 3, 2, 4, 3, 3, 5. Create a frequency distribution table and determine the mode.
The mode is 3 and the frequency distribution table is given below:
|
Books Read |
Frequency |
|
2 |
2 |
|
3 |
3 |
|
4 |
1 |
|
5 |
1 |
Explanation
First create the frequency distribution table by seeing how many times each number repeats:
|
Books Read |
Frequency |
|
2 |
2 |
|
3 |
3 |
|
4 |
1 |
|
5 |
1 |
To calculate the mode, we observe the distribution table, on which value has the most frequency. 3 is the number that occurs most frequently. Hence, 3 is the mode
FAQs on Discrete Data
1.What is discrete data?
2.How is discrete data different from continuous data?
3.How is discrete data typically represented?
4.Which statistical measures are commonly used with discrete data?
5.How do you calculate the mean of a discrete data?
6.How can children in Singapore use numbers in everyday life to understand Discrete Data?
7.What are some fun ways kids in Singapore can practice Discrete Data with numbers?
8.What role do numbers and Discrete Data play in helping children in Singapore develop problem-solving skills?
9.How can families in Singapore create number-rich environments to improve Discrete Data skills?
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Jaipreet Kour Wazir
About the Author
Jaipreet Kour Wazir is a data wizard with over 5 years of expertise in simplifying complex data concepts. From crunching numbers to crafting insightful visualizations, she turns raw data into compelling stories. Her journey from analytics to education ref
Fun Fact
: She compares datasets to puzzle games—the more you play with them, the clearer the picture becomes!
