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Probability Theory Update
Probability Theory Update
Cumulative Distribution Function (CDF) 1/2
What is it?
This function calculates the probability that the random variable X will take the value less than or equal to x. Example:
Calculate the probability that we will have success with the fair coin (the chance of getting head or tail is 50%) in at least in 4 out of 15 trials. We assume that success means getting a head.
Python realization:
# Import required library import scipy.stats as stats # The desired number of success trial x = 4 # The number of attempts n = 15 # The probability of getting a success p = 0.5 # The resulting probability probability = stats.binom.cdf(x, n, p) print("The probability is", probability * 100, "%")
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Cumulative Distribution Function (CDF) 1/2
What is it?
This function calculates the probability that the random variable X will take the value less than or equal to x. Example:
Calculate the probability that we will have success with the fair coin (the chance of getting head or tail is 50%) in at least in 4 out of 15 trials. We assume that success means getting a head.
Python realization:
# Import required library import scipy.stats as stats # The desired number of success trial x = 4 # The number of attempts n = 15 # The probability of getting a success p = 0.5 # The resulting probability probability = stats.binom.cdf(x, n, p) print("The probability is", probability * 100, "%")
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixoObrigado pelo seu feedback!
Cumulative Distribution Function (CDF) 1/2
What is it?
This function calculates the probability that the random variable X will take the value less than or equal to x. Example:
Calculate the probability that we will have success with the fair coin (the chance of getting head or tail is 50%) in at least in 4 out of 15 trials. We assume that success means getting a head.
Python realization:
# Import required library import scipy.stats as stats # The desired number of success trial x = 4 # The number of attempts n = 15 # The probability of getting a success p = 0.5 # The resulting probability probability = stats.binom.cdf(x, n, p) print("The probability is", probability * 100, "%")
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixoObrigado pelo seu feedback!
What is it?
This function calculates the probability that the random variable X will take the value less than or equal to x. Example:
Calculate the probability that we will have success with the fair coin (the chance of getting head or tail is 50%) in at least in 4 out of 15 trials. We assume that success means getting a head.
Python realization:
# Import required library import scipy.stats as stats # The desired number of success trial x = 4 # The number of attempts n = 15 # The probability of getting a success p = 0.5 # The resulting probability probability = stats.binom.cdf(x, n, p) print("The probability is", probability * 100, "%")
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixoMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo