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+#Normal Distribution QuickSort
+
+
+Algorithm implementing QuickSort Algorithm where the pivot element is chosen randomly between first and last elements of the array and the array elements are taken from a Standard Normal Distribution.
+This is different from the ordinary quicksort in the sense, that it applies more to real life problems , where elements usually follow a normal distribution. Also the pivot is randomized to make it a more generic one.
+
+
+##Array Elements
+
+The array elements are taken from a Standard Normal Distribution , having mean = 0 and standard deviation 1.
+
+####The code
+
+```python
+
+>>> import numpy as np 
+>>> from tempfile import TemporaryFile
+>>> outfile = TemporaryFile()    
+>>> p = 100 # 100 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)
+
+```
+
+------
+
+#### The Distribution of the Array elements.
+
+```python
+>>> mu, sigma = 0, 1 # mean and standard deviation
+>>> s = np.random.normal(mu, sigma, p)
+>>> count, bins, ignored = plt.hist(s, 30, normed=True)
+>>> plt.plot(bins , 1/(sigma * np.sqrt(2 * np.pi)) *np.exp( - (bins - mu)**2 / (2 * sigma**2) ),linewidth=2, color='r')
+>>> plt.show()   
+
+```
+
+
+-----
+
+
+
+
+![](https://www.mathsisfun.com/data/images/normal-distrubution-large.gif)
+
+---
+
+---------------------
+
+--
+
+##Plotting the function for Checking 'The Number of Comparisons' taking place between Normal Distribution QuickSort and Ordinary QuickSort 
+
+```python
+>>>import matplotlib.pyplot as plt
+
+    
+    # Normal Disrtibution QuickSort is red
+>>> plt.plot([1,2,4,16,32,64,128,256,512,1024,2048],[1,1,6,15,43,136,340,800,2156,6821,16325],linewidth=2, color='r')
+    
+    #Ordinary QuickSort is green
+>>> plt.plot([1,2,4,16,32,64,128,256,512,1024,2048],[1,1,4,16,67,122,362,949,2131,5086,12866],linewidth=2, color='g')
+
+>>> plt.show()
+
+```
+
+
+----
+
+
+------------------
+