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, "%")

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Everything was clear?

Thanks for your feedback!

Section 4. Chapter 4

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, "%")

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

Section 4. Chapter 4

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, "%")

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your 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:


              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, "%")

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Section 4. Chapter 4

Switch to desktop for real-world practiceContinue from where you are using one of the options below