# Learn How to Find Mode: A Complete Guide

Baca Cepat

## Introduction

Welcome to our comprehensive guide on how to find mode. In the field of statistics, mode is one of the most important measures of central tendency. It is a value that appears most frequently in a given data set. Finding mode helps in understanding the distribution of data and making informed decisions. In this article, we will explain how to find mode step-by-step, providing examples and tips. Whether you are a student, researcher, or professional, this guide will equip you with the knowledge needed to analyze data accurately.

Before we dive into the details, let’s first understand the basics of statistics. Statistics is a branch of mathematics that deals with the collection, analysis, and interpretation of data. It is used in various fields such as business, science, medicine, and social sciences to extract meaningful insights from data. A statistical measure is a mathematical value that describes a set of data. Measures of central tendency are the most common statistical measures used to describe the average value of a data set.

In this article, we will provide a detailed explanation of how to find mode, including the formula, steps, and examples. We will also discuss some common misconceptions about mode and provide answers to frequently asked questions. By the end of this article, you will have a clear understanding of how to find mode and apply it in your statistical analysis.

### The Importance of Finding Mode

Mode provides useful information about the data set. It helps in identifying the central value that occurs frequently in the data set. By finding mode, we can:

• Identify the most frequent value in the data set
• Understand the distribution of data
• Identify outliers or unusual values
• Make informed decisions based on the data

Mode is particularly useful when dealing with categorical data such as colours, shapes, or gender. It can also be used to find the peak value in a continuous data set such as height or weight. In short, mode helps in summarizing the key features of the data set.

### Formula for Finding Mode

The formula for finding mode depends on the type of data set. For a unimodal data set with one mode, the formula is:

Mode = Value with the highest frequency

For example, if we have the following data set:

Value Frequency
5 3
10 2
15 1
20 1

The mode is 5, as it has the highest frequency of 3.

For a bimodal data set with two modes, the formula is:

Mode = Average of the values with the highest frequency

For example, if we have the following data set:

Value Frequency
5 3
10 2
15 1
20 3

The mode is (5+20)/2 = 12.5, as both 5 and 20 have the highest frequency of 3.

For a multimodal data set with more than two modes, there is no fixed formula for finding mode. In such cases, all the values with the highest frequency can be considered as mode.

### Steps to Find Mode

The following are the steps to find mode:

1. Organize the data set in ascending or descending order
2. Count the frequency of each value
3. Identify the value(s) with the highest frequency
4. If there is one value with the highest frequency, it is the mode
5. If there are two or more values with the highest frequency, take their average to find the mode
6. If there is more than one mode, list all the values with the highest frequency as mode

Let’s understand these steps with an example.

### Example

Suppose we have the following data set:

2, 4, 6, 4, 7, 8, 3, 4, 2, 9

Let’s apply the steps to find mode:

1. Organize in ascending order: 2, 2, 3, 4, 4, 4, 6, 7, 8, 9
2. Count frequency: 2 (2), 1 (3), 3 (4), 1 (6), 1 (7), 1 (8), 1 (9)
3. Identify highest frequency: 3 (4)
4. Mode = 4

The mode of this data set is 4. If there were two values with the highest frequency, say 4 and 2, the mode would be their average, which is 3.

## How to Find Mode in Different Types of Data Sets

Mode can be calculated for different types of data sets. In this section, we will explain how to find mode in:

• Discrete data set
• Continuous data set
• Grouped frequency distribution
• Cumulative frequency distribution

### Discrete Data Set

A discrete data set is one that consists of distinct or separate values. Examples of discrete data sets include the number of students in a class, the number of apples in a basket, or the number of goals scored in a football match. To find mode in a discrete data set:

1. Organize the data set in ascending or descending order
2. Count the frequency of each value
3. Identify the value(s) with the highest frequency
4. If there is one value with the highest frequency, it is the mode
5. If there are two or more values with the highest frequency, take their average to find the mode
6. If there is more than one mode, list all the values with the highest frequency as mode

Let’s understand this with an example.

### Example

Suppose we have the following data set:

4, 6, 7, 4, 2, 6, 8, 4, 2, 9, 3, 4

Let’s apply the steps to find mode:

1. Organize in ascending order: 2, 2, 3, 4, 4, 4, 4, 6, 6, 7, 8, 9
2. Count frequency: 2 (2), 1 (3), 4 (4), 2 (6), 1 (7), 1 (8), 1 (9)
3. Identify highest frequency: 4 (4)
4. Mode = 4

The mode of this data set is 4.

### Continuous Data Set

A continuous data set is one that consists of a range of values. Examples of continuous data sets include height, weight, or temperature. To find mode in a continuous data set:

1. Create a frequency distribution table with class intervals and frequencies
2. Identify the class interval with the highest frequency
3. The midpoint of the class interval with the highest frequency is the mode

Let’s understand this with an example.

### Example

Suppose we have the following data set:

65, 68, 71, 70, 66, 69, 67, 72, 68, 70, 66, 69, 73, 68, 70, 72, 71, 69, 67

Let’s apply the steps to find mode:

1. Create a frequency distribution table:
Class Interval Frequency
65-67.99 3
68-70.99 6
71-73.99 4
1. Identify highest frequency: 6 (68-70.99)
2. Mode = (68+70.99)/2 = 69.495

The mode of this data set is 69.495.

### Grouped Frequency Distribution

A grouped frequency distribution is one that consists of class intervals and their frequencies. Examples of grouped frequency distributions include age groups, income ranges, or test scores. To find mode in a grouped frequency distribution:

1. Identify the class interval with the highest frequency
2. The midpoint of the class interval with the highest frequency is the mode

Let’s understand this with an example.

### Example

Suppose we have the following grouped frequency distribution:

Class Interval Frequency
10-19 5
20-29 12
30-39 18
40-49 10
50-59 7

Let’s apply the steps to find mode:

1. Identify highest frequency: 18 (30-39)
2. Mode = (30+39)/2 = 34.5

The mode of this grouped frequency distribution is 34.5.

### Cumulative Frequency Distribution

A cumulative frequency distribution is one that consists of class intervals, their cumulative frequencies, and the total frequency. Examples of cumulative frequency distributions include the number of cars sold per month, the number of website visitors per day, or the number of patients treated in a hospital.

To find mode in a cumulative frequency distribution:

1. Identify the class interval with the highest frequency
2. Find the lower class boundary of the class interval with the highest frequency
3. Find the frequency of the class interval with the highest frequency
4. Find the frequency of the class interval immediately preceding the class interval with the highest frequency
5. Find the frequency of the class interval immediately following the class interval with the highest frequency
6. The mode = Lower class boundary + [(Frequency of highest class interval – Frequency of preceding class interval) / (Frequency of highest class interval – Frequency of succeeding class interval)] x Class interval

Let’s understand this with an example.

### Example

Suppose we have the following cumulative frequency distribution:

Class Interval Cumulative Frequency Total Frequency
5-9 5 5
10-14 14 9
15-19 30 16
20-24 57 27
25-29 85 28

Let’s apply the steps to find mode:

1. Identify highest frequency: 28 (25-29)
2. Lower class boundary of 25-29 = 25
3. Frequency of 25-29 = 28
4. Frequency of 20-24 = 27
5. Frequency of 15-19 = 16
6. Mode = 25 + [(28-27)/(28-16)] x 5 = 25.18

The mode of this cumulative frequency distribution is 25.18.

There are some common misconceptions about mode. In this section, we will address these misconceptions and provide clarifications.

### Myth: Mode is always unique

Fact: Mode is not always unique. A data set can have no mode, one mode, or more than one mode. If two or more values have the same highest frequency, they are all considered as mode.

### Myth: Mode is always in the data set

Fact: Mode may or may not be in the data set. For example, if we have the following data set:

2, 4, 6, 8, 10

The mode of this data set is not in the data set, as there is no value that appears more than once.

### Myth: Mode is the most common value

Fact: Mode is the value that appears most frequently in a data set, but it is not necessarily the most common value. For example, if we have the following data set:

3, 3, 3, 3, 3, 100

The most common value in this data set is 3, but the mode is also 3.

## FAQs

### 1. What is mode?

Mode is a measure of central tendency that refers to the most frequently occurring value in a data set.

### 2. How do you find mode?

To find mode, organize the data set, count the frequency of each value, identify the value(s) with the highest frequency, and determine the mode.

### 3. What is the formula for finding mode?

For a unimodal data set with one mode, the formula for finding mode is:

Mode = Value with the highest frequency

For a bimodal data set with two modes, the formula for finding mode is:

Mode = Average of the values with the highest frequency

Video:Learn How to Find Mode: A Complete Guide