Contenido del Curso
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, "%")
Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones¡Gracias por tus comentarios!
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, "%")
Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones¡Gracias por tus comentarios!
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, "%")
Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opcionesCambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones