sympy.stats.variance() function in Python Last Updated : 01 Jun, 2020 Comments Improve Suggest changes Like Article Like Report In mathematics, the variance is the way to check the difference between the actual value and any random input, i.e variance can be calculated as a squared difference of these two values. With the help of sympy.stats.variance() method, we can calculate the value of variance by using this method. Syntax : sympy.stats.variance(value) Return : Return the value of variance. Example #1 : In this example we can see that by using sympy.stats.variance() method, we are able to calculate the value of variance using this method. Python3 1=1 # Import Sympy and variance from sympy.stats import P, variance, Die X, Y = Die('X', 5), Die('Y', 3) # Using stats.variance() method gfg = variance(X + Y) print(gfg) Output : 8/3 Example #2 : Python3 1=1 # Import Sympy and variance from sympy.stats import P, variance, Die X, Y = Die('X', 2), Die('Y', 4) # Using stats.variance() method gfg = variance(X * Y) print(gfg) Output : 75/16 Comment More infoAdvertise with us Next Article sympy.stats.variance() function in Python J jitender_1998 Follow Improve Article Tags : Python Python SymPy-Stats Practice Tags : python Similar Reads sympy.stats.FiniteRV() function in Python With the help of sympy.stats.FiniteRV() method, we can create a random variable gives a dictionary of density by using sympy.stats.FiniteRV() method. Syntax : sympy.stats.FiniteRV(name, dict) Return : Return the variable having dictionary of density. Example #1 : In this example, we can see that by 1 min read sympy.stats.Binomial() function in Python With the help of sympy.stats.Binomial() method, we can create a Finite Random Variable representing a binomial distribution. A binomial distribution is the probability of a SUCCESS or FAILURE outcome in an experiment or survey that is repeated multiple times. Syntax: sympy.stats.Binomial(name, n, p 1 min read sciPy stats.variation() function | Python scipy.stats.variation(arr, axis = None) function computes the coefficient of variation. It is defined as the ratio of standard deviation to mean. Parameters : arr : [array_like] input array. axis : [int or tuples of int] axis along which we want to calculate the coefficient of variation. -> axis = 0 2 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 statistics mean() function - Python The mean() function from Python’s statistics module is used to calculate the average of a set of numeric values. It adds up all the values in a list and divides the total by the number of elements. For example, if we have a list [2, 4, 6, 8], the mean would be (2 + 4 + 6 + 8) / 4 = 5.0. This functio 4 min read Like