Beta distribution

Author: heysushil

23.Beta_distribution.py

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+'''
+Beta distribution using matplotlib.pyplot, numpy.random module and seaborn librarys by hey sushil:
+
+Probability theory ke andar aur statistics me isko continuous probability distribution familiy me rakha gaya hai.
+
+Beta distribution ko [0, 1] interval ke beach me define kiya jata hai.
+
+Beta distribution ko 2 possitive paramerters se denote kiya jata hai:
+1. alpha
+2. beta
+
+Beta distribution ke andar ye dono parameters ye kaam karte hain:
+1. Random varibale ke exponent ke roop me hota hai.
+2. Durshra, ye distribution ke shape ko control karta hai.
+3. Agar isko multiple varaible me generalize kiya jaye to uss case me ye- Dirichlet distributon ban jata hai.
+
+Beta distribution ka use random variable ya matrix model ke andar ek limited length me hi kai shape me change kiya ja sake uske liye kiya jata hai.
+
+Beta distribution ka best use random variables ke sath percantages and proportions nikalne me kiya jata hai.
+
+Kuch important points:
+
+1. Beta distribution, ek special case hai Dirichlet distribution ka.
+2. Beta distribution, Gamma distribution se related hai.
+3. Beta distribution, ka use Bayesian interface aur order statistics me bhi kiya jata hai.
+
+Note: Beta function bhi hota hai but wo math me hota hai. Iss ko Eular integral of fist kind bhi kahte hain.
+Ye special type ka function hai jo gamma function aur Binomial coefficent ke pass hota hai.
+
+numpy.random.beta method arguments:
+a: Float or array like float values and non-negative (for Alpha)
+b: Float or array like float values and non-negative (for Beta)
+size: int or tuple of int values in return
+'''
+
+import numpy.random as r
+import seaborn as sns
+import matplotlib.pyplot as plt
+
+# print('\n', r.beta(a=0.5, b=0.5, size=(10)))
+
+# a and b both on same range
+sns.distplot(r.beta(a=0.5, b=0.5, size=(100,100)), hist=False, label='a=0.5 b=0.5')
+
+# a point high and b point low to show hight to low ratio
+sns.distplot(r.beta(a=5, b=1, size=(100,100)), hist=False, label='a=5 b=1')
+
+sns.distplot(r.beta(a=1, b=5, size=(100,100)), hist=False, label='a=1 b=5')
+
+sns.distplot(r.beta(a=2, b=2, size=(100,100)), hist=False, label='a=2 b=2')
+
+sns.distplot(r.beta(a=2, b=5, size=(100,100)), hist=False, label='a=2 b=5')
+
+# plt mehtods to beutify the result
+# plt.xlim(0,1)
+# plt.ylim(0,2.5)
+plt.xlabel('Range of X')
+plt.ylabel('Frequcry of Y')
+plt.title('Beta Distribution')
+
+plt.show()