Contenido del Curso
Probability Theory Update
Probability Theory Update
Probability Mass Function (PMF) 1/2
What is it? The function calculates the probability that a discrete random variable equals the exact value. Example:
Calculate the probability that we will have success with the fair coin (the chance of getting head or tail is 50%) 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.pmf(x, n, p) print("The probability is", probability * 100, "%")
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Probability Mass Function (PMF) 1/2
What is it? The function calculates the probability that a discrete random variable equals the exact value. Example:
Calculate the probability that we will have success with the fair coin (the chance of getting head or tail is 50%) 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.pmf(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!
Probability Mass Function (PMF) 1/2
What is it? The function calculates the probability that a discrete random variable equals the exact value. Example:
Calculate the probability that we will have success with the fair coin (the chance of getting head or tail is 50%) 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.pmf(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? The function calculates the probability that a discrete random variable equals the exact value. Example:
Calculate the probability that we will have success with the fair coin (the chance of getting head or tail is 50%) 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.pmf(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