sciPy stats.alpha() | Python Last Updated : 14 Mar, 2019 Comments Improve Suggest changes Like Article Like Report scipy.stats.alpha() is an alpha continuous random variable that is defined with a standard format and some shape parameters to complete its specification. Parameters : q : lower and upper tail probability x : quantiles a : shape parameter loc : [optional] location parameter. Default = 0 scale : [optional] scale parameter. Default = 1 size : [tuple of ints, optional] shape or random variates. moments : [optional] composed of letters [‘mvsk’]; 'm' = mean, 'v' = variance, 's' = Fisher's skew and 'k' = Fisher's kurtosis. (default = 'mv'). Results : alpha continuous random variable Code #1 : Creating alpha continuous random variable Python3 1== # Python code to demonstrate scipy.alpha() from scipy.stats import alpha # using alpha() method numargs = alpha.numargs [ a ] = [0.6, ] * numargs rv = alpha(a) Code #2 : Python3 1== # Python code to demonstrate scipy.alpha() import numpy as np import matplotlib.pyplot as plt # getting distribution using linspace() distribution = np.linspace(0, np.minimum(rv.dist.b, 3)) plot = plt.plot(distribution, rv.pdf(distribution)) Output : Comment More infoAdvertise with us Next Article sciPy stats.alpha() | Python V vishal3096 Follow Improve Article Tags : Python Python-scipy Python scipy-stats-functions Practice Tags : python Similar Reads scipy stats.gamma() | Python scipy.stats.gamma() is an gamma continuous random variable that is defined with a standard format and some shape parameters to complete its specification. Parameters : -> q : lower and upper tail probability -> x : quantiles -> loc : [optional]location parameter. Default = 0 -> scale : [ 2 min read scipy stats.chi() | Python scipy.stats.chi() is an chi continuous random variable that is defined with a standard format and some shape parameters to complete its specification. Parameters : q : lower and upper tail probability x : quantiles loc : [optional] location parameter. Default = 0 scale : [optional] scale parameter. 2 min read scipy stats.f() | Python scipy.stats.f() is an F continuous random variable that is defined with a standard format and some shape parameters to complete its specification. Parameters : q : lower and upper tail probability a, b : shape parameters x : quantiles loc : [optional] location parameter. Default = 0 scale : [optiona 2 min read scipy stats.erlang() | Python scipy.stats.erlang() : is an Erlang continuous random variable that is defined with a standard format and some shape parameters to complete its specification. it is a special case of the Gamma distribution. Parameters : q : lower and upper tail probability x : quantiles loc : [optional] location par 2 min read scipy stats.beta() | Python The scipy.stats.beta() is a beta continuous random variable that is defined with a standard format and some shape parameters to complete its specification. f(x,α,β)=(Γ(α+β)xα−1(1−x)β−1​)/Γ(α)Γ(β) where: α>0 and β>0β>0 are the shape parameters of the Beta distribution.Γ Gamma is the Gamma fu 2 min read Like