# How to Find Median: Explained Step-by-Step with Examples

Greetings, dear reader! Whether you’re a math student struggling with median calculations, or someone who simply wants to know how to find median, you’ve come to the right place. Median is a fundamental concept in statistics, used in various fields such as finance, healthcare, and social sciences. In this article, we’ll explain how to find median, step-by-step, with examples and illustrations. So, let’s get started! 🔍

Baca Cepat

## Introduction

Median is a measure of central tendency or average, which represents the middle value of a dataset. In other words, it divides the dataset into two equal parts, with half of the values above and half below the median. Median is different from mean (arithmetic average), which is the sum of all values divided by the number of values. Median is more robust than mean, as it is less affected by outliers or extreme values. Median is denoted by the symbol ‘Me’ or ‘Md’, and is used in many statistical analyses such as hypothesis testing, regression analysis, and data visualization.

There are different methods to calculate the median, depending on the type of data and the level of measurement. For example, if the data is numeric and continuous, we can use the formula:

### Median Formula for Even Number of Values

For Even Number of Values:
Step 1: Arrange the values in ascending order
Step 2: Find the two middle values
Step 3: Calculate the average of the two middle values
Step 4: The result is the median

For example, let’s say we have a dataset of 8 values: 5, 3, 7, 1, 9, 4, 6, 2. To find the median, we follow these steps:

Step 1: Arrange the values in ascending order: 1, 2, 3, 4, 5, 6, 7, 9.

Step 2: Find the two middle values: 4 and 5.

Step 3: Calculate the average of the two middle values: (4 + 5)/2 = 4.5.

Step 4: The result is the median: 4.5.

If the dataset has an odd number of values, we simply take the middle value as the median. For example, if we have a dataset of 7 values: 5, 3, 7, 1, 9, 4, 6, the median is 5.

## How to Find Median: Step-by-Step Guide

Now that we’ve explained the concept of median and the formula for calculating it, let’s dive deeper into the process of finding median. We’ll provide a step-by-step guide with examples and illustrations, so that you can follow along easily.

### Step 1: Arrange the Values in Ascending Order

The first step in finding median is to arrange the values in ascending order, from the smallest to the largest. This is important because we need to identify the middle values, and we cannot do that unless the values are in order. If the dataset has duplicate values, we can keep one copy and remove the others. For example, if we have a dataset of 6 values: 3, 1, 2, 3, 4, 5, we can remove one copy of 3 and get 5 distinct values: 1, 2, 3, 4, 5.

#### Example:

Let’s say we have a dataset of 10 values, representing the ages of 10 people in a group:

22, 25, 27, 29, 31, 32, 35, 37, 39, 40

To find the median, we first arrange the values in ascending order:

22, 25, 27, 29, 31, 32, 35, 37, 39, 40

### Step 2: Find the Middle Values

Once we have arranged the values in order, we can find the middle values. The number of middle values depends on whether the dataset has an odd or even number of values. If the dataset has an odd number of values, there is only one middle value. If the dataset has an even number of values, there are two middle values. To find the middle values, we can use the formula:

### Formula for Finding Middle Values

For Odd Number of Values: For Even Number of Values:
Step 1: Count the number of values Step 1: Count the number of values
Step 2: Divide the number of values by 2 Step 2: Divide the number of values by 2
Step 3: The result is the position of the middle value Step 3: The results are the positions of the two middle values

For example, if we have a dataset of 7 values, the middle value is the 4th value, as (7 + 1)/2 = 4. If we have a dataset of 8 values, the two middle values are the 4th and 5th values, as (8/2) = 4 and (8/2) + 1 = 5.

#### Example:

Let’s continue with our previous example of ages:

22, 25, 27, 29, 31, 32, 35, 37, 39, 40

To find the middle values, we first count the number of values:

n = 10

Since n is even, there are two middle values. We divide n by 2:

n/2 = 5

This means that the two middle values are the 5th and 6th values. We can verify this by looking back at the ordered dataset:

22, 25, 27, 29, 31, 32, 35, 37, 39, 40

Thus, the two middle values are 32 and 35.

### Step 3: Calculate the Median

Once we have identified the middle values, we can calculate the median. If the dataset has an odd number of values, the median is the middle value. If the dataset has an even number of values, the median is the average of the two middle values.

#### Example:

Let’s continue with our previous example of ages:

22, 25, 27, 29, 31, 32, 35, 37, 39, 40

Since there are two middle values (32 and 35), we take their average:

(32 + 35)/2 = 33.5

Therefore, the median age of the group is 33.5 years.

### 1. What is median?

Median is a measure of central tendency or average, which represents the middle value of a dataset. In other words, it divides the dataset into two equal parts, with half of the values above and half below the median.

### 2. How is median different from mean?

Median is different from mean (arithmetic average), which is the sum of all values divided by the number of values. Median is more robust than mean, as it is less affected by outliers or extreme values.

### 3. How do you find the median of a dataset?

To find the median of a dataset, you need to arrange the values in ascending order, find the middle values, and then calculate the median based on whether the dataset has an odd or even number of values.

### 4. What if the dataset has duplicate values?

If the dataset has duplicate values, you can keep one copy and remove the others. This will ensure that the dataset has distinct values, which is necessary for finding the median.

### 5. What if the dataset has missing values?

If the dataset has missing values, you can either remove them or impute them with some value, depending on the nature and purpose of your analysis.

### 6. What is the use of median in statistics?

Median is used in many statistical analyses such as hypothesis testing, regression analysis, and data visualization. It provides a robust measure of central tendency, which is less affected by outliers or extreme values.

### 7. Can median be negative?

Yes, median can be negative if the dataset contains negative values. However, it is important to interpret the median in the context of the data and the research question.

### 8. What if the dataset has an even number of values and the two middle values are not integers?

If the dataset has an even number of values and the two middle values are not integers, you can still take their average, which will be a decimal or a fraction. This is a valid method of calculating the median.

### 9. Can median and mean be the same?

Yes, median and mean can be the same if the dataset is symmetrical or normally distributed. However, this is not always the case, especially if the dataset has outliers or skewness.

### 10. What if the dataset has outliers?

If the dataset has outliers, the median is a better measure of central tendency than mean, as it is less affected by outliers. However, it is still important to investigate the outliers and their possible causes, as they may reveal important information about the data or the population.

### 11. Can median be used for nominal or ordinal data?

Yes, median can be used for nominal or ordinal data, although it is less informative than for numerical data. In this case, median represents the middle value or category of the data.

### 12. What if the dataset has a small sample size?

If the dataset has a small sample size (less than 30), the median may not be a reliable measure of central tendency, as it is based on a limited number of values. In this case, other measures such as mode or range may be more appropriate.

### 13. Can median be used for time-series data?

Yes, median can be used for time-series data, although it may not capture the trends or patterns in the data. In this case, other measures such as moving average or trend analysis may be more appropriate.

## Conclusion

In conclusion, finding median is an essential skill for anyone working with data or statistics. It provides a robust measure of central tendency, which is less affected by outliers or extreme values. In this article, we have explained how to find median, step-by-step, with examples and illustrations. We hope that this article has been helpful and informative for you. If you have any questions, feel free to contact us or leave a comment below. Happy calculating! 🧮

## Closing/Disclaimer

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