# How Do You Find The 25th Median 75th Percentile Sql

When working with SQL, finding the 25th percentile, median, and 75th percentile can be a powerful way to analyze data distribution and gain valuable insights. Let’s dive into how to accomplish this, and explore the significance of these calculations in real-world scenarios.

## Finding the 25th Percentile (First Quartile)

When I need to find the 25th percentile in SQL, I often start by sorting the data in ascending order. After that, I use the PERCENTILE_CONT() or PERCENTILE_DISC() function, depending on the specific requirements of the analysis. Here’s a simplified example of how this can be achieved:

```SELECT PERCENTILE_CONT(0.25) WITHIN GROUP (ORDER BY column_name) AS percentile_25 FROM table_name;```

## Finding the Median (50th Percentile)

Calculating the median in SQL involves similar steps to finding the 25th percentile. I sort the data and then use the same PERCENTILE_CONT() or PERCENTILE_DISC() function, but this time with a parameter of 0.5 to represent the median:

```SELECT PERCENTILE_CONT(0.5) WITHIN GROUP (ORDER BY column_name) AS median FROM table_name;```

## Finding the 75th Percentile (Third Quartile)

Similar to finding the 25th percentile, the 75th percentile can be obtained by adjusting the parameter in the PERCENTILE_CONT() or PERCENTILE_DISC() function:

```SELECT PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY column_name) AS percentile_75 FROM table_name;```

## Real-World Application

Understanding percentiles and median in SQL is crucial for various applications, ranging from business analytics to healthcare data analysis. For example, in a retail setting, knowing the 25th and 75th percentile of customer purchase amounts can help identify spending patterns and target marketing strategies effectively. Similarly, in healthcare, analyzing patient wait times using percentiles can aid in optimizing staff scheduling and resource allocation.

## Conclusion

Mastering the calculation of percentiles and median in SQL empowers data professionals to extract meaningful insights from large datasets. By leveraging these techniques, it becomes possible to uncover valuable trends and patterns that can drive informed decision-making. Whether it’s for business, healthcare, or any other industry, the ability to find these key statistical measures is an essential skill in the data-driven world.