sympy.stats.Poisson() in Python Last Updated : 29 Jul, 2024 Summarize Comments Improve Suggest changes Share Like Article Like Report With the help of sympy.stats.Poisson() method, we can get the random variable representing the poisson distribution. Syntax : sympy.stats.Poisson(name, lambda)Return : Return the random variable. Example #1 :In this example we can see that by using sympy.stats.Poisson() method, we are able to get the random variable representing poisson distribution by using this method. Python3 1=1 # Import sympy and poisson from sympy.stats import Poisson, density, E, variance from sympy import Symbol, simplify # Using sympy.stats.Poisson() method rate = Symbol("lambda", positive = True) X = Poisson("x", rate) gfg = density(X)(4) print(gfg) Output : lambda**4*exp(-lambda)/24 Example #2 : Python3 1=1 # Import sympy and poisson from sympy.stats import Poisson, density, E, variance from sympy import Symbol, simplify # Using sympy.stats.Poisson() method rate = Symbol("lambda", positive = True) X = Poisson("x", rate) gfg = density(X)(6) print(gfg) Output : lambda**6*exp(-lambda)/720 Comment More infoAdvertise with us Next Article sympy.stats.Poisson() in Python J jitender_1998 Follow Improve Article Tags : Python SymPy Python SymPy-Stats Practice Tags : python Similar Reads sympy.stats.Logistic() in python With the help of sympy.stats.Logistic() method, we can get the continuous random variable which represents the logistic distribution. Syntax : sympy.stats.Logistic(name, mu, s) Where, mu and s are real number and mu, s > 0. Return : Return the continuous random variable. Example #1 : In this exam 1 min read sympy.stats.Chi() in Python With the help of sympy.stats.Chi() method, we can get the continuous random variable which represents the chi distribution. Syntax : sympy.stats.Chi(name, k) Where, k is number of degree of freedom. Return : Return the continuous random variable. Example #1 : In this example we can see that by using 1 min read sympy.stats.PowerFunction() in Python With the help of sympy.stats.PowerFunction() method, we can get the continuous random variable which represents the Power Function distribution. Syntax : sympy.stats.PowerFunction(name, alpha, a, b) Where, a, b and alpha are real number. Return : Return the continuous random variable. Example #1 : I 1 min read sympy.stats.Pareto() in python With the help of sympy.stats.Pareto() method, we can get the continuous random variable which represents the Pareto distribution. Syntax : sympy.stats.Pareto(name, xm, alpha) Where, xm and alpha are real number and xm, alpha > 0. Return : Return the continuous random variable. Example #1 : In thi 1 min read sympy.stats.Moyal() in python With the help of sympy.stats.Moyal() method, we can get the continuous random variable which represents the moyal distribution. Syntax : sympy.stats.Moyal(name, mu, sigma) Where, mu and sigma are real number. Return : Return the continuous random variable. Example #1 : In this example we can see tha 1 min read Like