Python Coding challenge - Day 398| What is the output of the following Python Code?

 

Code Explanation:

from scipy.stats import poisson

This imports the poisson module from the scipy.stats library.

The poisson module provides functions to work with the Poisson distribution, such as computing probabilities and generating random values.

lambda_value = 4  

lambda_value (λ) represents the expected number of occurrences in a given time period or space.

Here, λ = 4, meaning we expect 4 occurrences on average.

Example scenario: If a store receives 4 customers per hour on average, λ = 4.

x = 2  

x = 2 represents the specific number of occurrences we are calculating the probability for.

This means we are interested in finding the probability of exactly 2 occurrences happening.

Example scenario: If a store gets an average of 4 customers per hour, what is the probability that exactly 

prob = poisson.pmf(x, lambda_value)  

poisson.pmf(x, lambda_value) calculates the Poisson Probability Mass Function (PMF).

The PMF gives the probability of observing exactly x occurrences when the average occurrence rate is λ.

print(round(prob, 4))  

round(prob, 4) rounds the computed probability to 4 decimal places for better readability.

The final probability value is 0.1465, meaning:

There is a 14.65% chance of exactly 2 occurrences happening when the average rate is 4.

Final Output:

0.1465

This means:

If events happen on average 4 times per time unit, the chance of exactly 2 events happening is 0.1465 (or 14.65%).