## Quartile :

Quartiles are statistical measures that divide a dataset into four equal parts, or quarters. They are used to identify the distribution of values within a dataset and to compare datasets to one another.

There are three types of quartiles: the lower quartile (also known as the first quartile or Q1), the median (also known as the second quartile or Q2), and the upper quartile (also known as the third quartile or Q3).

To calculate the quartiles, we first need to arrange the data in ascending order. For example, consider the following dataset:

10, 15, 20, 25, 30, 35, 40, 45, 50

To find the lower quartile, we divide the dataset into two equal parts. The first part contains the first four values (10, 15, 20, 25), and the second part contains the remaining five values (30, 35, 40, 45, 50). The lower quartile is the median of the first part, which is the average of the two middle values (20 and 25). Therefore, Q1 = 22.5.

To find the median, we again divide the dataset into two equal parts. The first part contains the first five values (10, 15, 20, 25, 30), and the second part contains the remaining four values (35, 40, 45, 50). The median is the middle value of the dataset, which is 30. Therefore, Q2 = 30.

To find the upper quartile, we divide the dataset into two equal parts. The first part contains the first six values (10, 15, 20, 25, 30, 35), and the second part contains the remaining three values (40, 45, 50). The upper quartile is the median of the second part, which is the average of the two middle values (45 and 50). Therefore, Q3 = 47.5.

Now that we have calculated the three quartiles, we can use them to summarize the distribution of values within the dataset. For example, we can use the interquartile range (IQR), which is the difference between Q3 and Q1, to measure the spread of the data. In this case, the IQR is 47.5 – 22.5 = 25. This tells us that the values in the dataset range from 22.5 to 47.5, with most of the values falling within this range.

Another way to use quartiles is to compare datasets to one another. For example, consider two datasets:

Dataset A: 10, 20, 30, 40, 50

Dataset B: 15, 25, 35, 45, 55

If we calculate the quartiles for both datasets, we will find that Q1, Q2, and Q3 are the same for both datasets. However, the values in dataset B are all larger than the values in dataset A. This tells us that dataset B has a higher average value than dataset A.

In conclusion, quartiles are statistical measures that divide a dataset into four equal parts and are used to identify the distribution of values within a dataset and to compare datasets to one another. They are calculated by dividing the dataset into two equal parts and finding the median of each part. The lower quartile is the median of the first part, the median is the middle value of the dataset, and the upper quartile is the median of the second part. Quartiles can be used to measure the spread of the data using the interquartile range and to compare datasets to one another.