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?

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?

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?

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