With the help of sympy.stats.Beta() method, we can get the continuous random variable which represents the beta distribution.
Syntax :
sympy.stats.Beta(name, alpha, beta)
Where, alpha and beta is greater than 0.
Return : Return the continuous random variable.
Example #1 :
In this example we can see that by using sympy.stats.Beta() method, we are able to get the continuous random variable represents the beta distribution by using this method.
# Import sympy and beta from sympy.stats import Beta, density, E, variance
from sympy import Symbol, simplify, pprint, factor
alpha = Symbol("alpha", positive = True)
beta = Symbol("beta", positive = True)
z = Symbol("z")
# Using sympy.stats.Beta() method X = Beta("x", alpha, beta)
gfg = density(X)(z)
pprint(gfg, use_unicode = False)
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Output :
alpha – 1 beta – 1
z *(1 – z)
————————–
B(alpha, beta)
Example #2 :
# Import sympy and beta from sympy.stats import Beta, density, E, variance
from sympy import Symbol, simplify, pprint, factor
alpha = 4
beta = 5
z = Symbol("z")
# Using sympy.stats.Beta() method X = Beta("x", alpha, beta)
gfg = density(X)(z)
pprint(gfg, use_unicode = False)
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Output :
3 4
z *(1 – z)
———–
B(4, 5)