diff --git a/sorts/random_normaldistribution_quicksort.py b/sorts/random_normaldistribution_quicksort.py
new file mode 100644
index 000000000..19b180578
--- /dev/null
+++ b/sorts/random_normaldistribution_quicksort.py
@@ -0,0 +1,66 @@
+from random import randint
+from tempfile import TemporaryFile
+import numpy as np
+import math
+
+
+
+def _inPlaceQuickSort(A,start,end):  
+    count = 0
+    if start<end:
+        pivot=randint(start,end)
+        temp=A[end]
+        A[end]=A[pivot]
+        A[pivot]=temp
+        
+        p,count= _inPlacePartition(A,start,end)
+        count += _inPlaceQuickSort(A,start,p-1)
+        count += _inPlaceQuickSort(A,p+1,end)
+    return count
+
+def _inPlacePartition(A,start,end):
+    
+    count = 0
+    pivot= randint(start,end)
+    temp=A[end]
+    A[end]=A[pivot]
+    A[pivot]=temp
+    newPivotIndex=start-1
+    for index in range(start,end):
+               
+        count += 1
+        if A[index]<A[end]:#check if current val is less than pivot value
+            newPivotIndex=newPivotIndex+1
+            temp=A[newPivotIndex]
+            A[newPivotIndex]=A[index]
+            A[index]=temp
+    
+    temp=A[newPivotIndex+1]
+    A[newPivotIndex+1]=A[end]
+    A[end]=temp
+    return newPivotIndex+1,count
+    
+outfile = TemporaryFile()    
+p = 100 # 1000 elements are to be sorted
+
+
+
+
+mu, sigma = 0, 1 # mean and standard deviation
+X = np.random.normal(mu, sigma, p)
+np.save(outfile, X)
+print('The array is')
+print(X)
+
+  
+    
+
+
+
+outfile.seek(0)  # using the same array
+M = np.load(outfile)
+r = (len(M)-1)
+z = _inPlaceQuickSort(M,0,r) 
+
+print("No of Comparisons for 100 elements selected from a standard normal distribution is :")
+print(z)