sympy.stats.LogNormal() in python Last Updated : 05 Jun, 2020 Comments Improve Suggest changes Like Article Like Report With the help of sympy.stats.LogNormal() method, we can get the continuous random variable which represents the Log-Normal distribution. Syntax : sympy.stats.LogNormal(name, mean, std) Where, mean and standard deviation are real number. Return : Return the continuous random variable. Example #1 : In this example we can see that by using sympy.stats.LogNormal() method, we are able to get the continuous random variable representing Log-Normal distribution by using this method. Python3 1=1 # Import sympy and LogNormal from sympy.stats import LogNormal, density from sympy import Symbol, pprint z = Symbol("z") mean = Symbol("mean", positive = True) std = Symbol("std", positive = True) # Using sympy.stats.LogNormal() method X = LogNormal("x", mean, std) gfg = density(X)(z) pprint(gfg) Output : 2 -(-mean + log(z)) ------------------- 2 ___ 2*std \/ 2 *e -------------------------- ____ 2*\/ pi *std*z Example #2 : Python3 1=1 # Import sympy and LogNormal from sympy.stats import LogNormal, density from sympy import Symbol, pprint z = 2.1 mean = 7.6 std = 4 # Using sympy.stats.LogNormal() method X = LogNormal("x", mean, std) gfg = density(X)(z) pprint(gfg) Output : 0.0136890249307238*\/ 2 ------------------------ ____ \/ pi Comment More infoAdvertise with us Next Article sympy.stats.LogNormal() in python J jitender_1998 Follow Improve Article Tags : Python SymPy Python SymPy-Stats Practice Tags : python Similar Reads sympy.stats.Normal() in python With the help of sympy.stats.Normal() method, we can get the continuous random variable which represents the normal distribution. Syntax : sympy.stats.Normal(name, mean, std) Where, mean and std are real number. Return : Return the continuous random variable. Example #1 : In this example we can see 1 min read sympy.stats.Logarithmic() in Python With the help of sympy.stats.Logarithmic() method, we can get the random variable representing the logarithmic distribution. Syntax : sympy.stats.Logarithmic(name, p) Return : Return the random variable. Example #1 : In this example we can see that by using sympy.stats.Logarithmic() method, we are a 1 min read 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.LogLogistic() in python With the help of sympy.stats.LogLogistic() method, we can get the continuous random variable which represents the Log-Logistic distribution. Syntax : sympy.stats.LogLogistic(name, alpha, beta) Where, alpha and beta are real number and alpha, beta > 0. Return : Return the continuous random variabl 1 min read Python - Log Normal Distribution in Statistics scipy.stats.lognorm() is a log-Normal continuous random variable. It is inherited from the of generic methods as an instance of the rv_continuous class. It completes the methods with details specific for this particular distribution. Parameters : q : lower and upper tail probability x : quantiles lo 2 min read Like