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Learn Cumulative Distribution Function (CDF) 1/2 | Probability Functions
Probability Theory Update

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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:

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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.cdf(x, n, p) print("The probability is", probability * 100, "%")
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SectionΒ 4. ChapterΒ 4

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book
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:

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.cdf(x, n, p) print("The probability is", probability * 100, "%")
copy

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

SectionΒ 4. ChapterΒ 4
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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