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Apprendre Probability Mass Function (PMF) 1/2 | Probability Functions
Probability Theory Update
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Contenu du cours

Probability Theory Update

Probability Theory Update

1. Probability Basics
2. Statistical Dependence
3. Learn Crucial Terms
4. Probability Functions
5. Distributions

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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:

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# 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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Section 4. Chapitre 2
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book
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:

1234567891011121314
# 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, "%")
copy

Switch to desktopPassez à un bureau pour une pratique réelleContinuez d'où vous êtes en utilisant l'une des options ci-dessous
Tout était clair ?

Comment pouvons-nous l'améliorer ?

Merci pour vos commentaires !

Section 4. Chapitre 2
Switch to desktopPassez à un bureau pour une pratique réelleContinuez d'où vous êtes en utilisant l'une des options ci-dessous
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