diff --git a/maths/inter_quartile_range.py b/maths/inter_quartile_range.py
new file mode 100644
index 000000000..08a7961bd
--- /dev/null
+++ b/maths/inter_quartile_range.py
@@ -0,0 +1,60 @@
+"""
+This is the implementation of inter_quartile range (IQR).
+
+function takes the list of numeric values as input
+and return the IQR as output.
+
+Script inspired from its corresponding Wikipedia article
+https://en.wikipedia.org/wiki/Interquartile_range
+"""
+
+from typing import List
+
+
+def find_median(x: List[float]) -> float:
+    """
+    This is the implementation of median.
+    :param x: The list of numeric values
+    :return: Median of the list
+    >>> find_median([1,2,2,3,4])
+    2
+
+    >>> find_median([1,2,2,3,4,4])
+    2.5
+    """
+    length = len(x)
+    if length % 2:
+        return x[length // 2]
+    return float((x[length // 2] + x[(length // 2) - 1]) / 2)
+
+
+def inter_quartile_range(x: List[float]) -> float:
+    """
+    This is the implementation of inter_quartile
+    range for a list of numeric.
+    :param x: The list of data point
+    :return: Inter_quartile range
+
+    >>> inter_quartile_range([4,1,2,3,2])
+    2.0
+
+    >>> inter_quartile_range([25,32,49,21,37,43,27,45,31])
+    18.0
+    """
+    length = len(x)
+    if length == 0:
+        raise ValueError
+    x.sort()
+    if length % 2:
+        q1 = find_median(x[0: length // 2])
+        q3 = find_median(x[(length // 2) + 1: length])
+    else:
+        q1 = find_median(x[0: length // 2])
+        q3 = find_median(x[length // 2: length])
+    return q3 - q1
+
+
+if __name__ == "__main__":
+    import doctest
+
+    doctest.testmod()