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) |
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 = 4beta = 5z = Symbol("z") # Using sympy.stats.Beta() method X = Beta("x", alpha, beta) gfg = density(X)(z) pprint(gfg, use_unicode = False) |
Output :
3 4
z *(1 – z)
———–
B(4, 5)
