The probability that a randomly selected NBA game lasts more than 150 minutes is 0.4.
#Cdf for uniform distribution pdf#
Not sure what should be the exact argument of cdf and pdf function and why. stats import uniform calculate uniform probability uniform. On changing the x in both the function I get my pdf plot as it is but cdf gets distorted. This method is very useful in theoretical work. A general method is the inverse transform sampling method, which uses the cumulative distribution function (CDF) of the target random variable.
But the function uniform.pdf and uniform.cdf takes x which seems unintuitive. The uniform distribution is useful for sampling from arbitrary distributions.
The uniformdistribution variable takes the actual distribution. The uniform_distribution variable takes the actual distribution.īut the function uniform.pdf and uniform.cdf takes x which seems unintuitive. As far as my understanding, the variable x is for x-axis values to plot pdf and cdf, which can be seen passes in both the function. As far as my understanding, the variable x is for x-axis values to plot pdf and cdf, which can be seen passes in both the function. Upon experimenting with some values I am getting this right. Uniform_distribution = uniform.rvs(0, 1, 1000) Following is the code: from scipy.stats import uniform I am trying to plot pdf and cdf of uniform continuous distribution.
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