Compute Poisson Probabilities in C

CBeginner
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Introduction

In this lab, you will learn how to compute Poisson probabilities in C. The Poisson distribution is a probability distribution that expresses the likelihood of a given number of events occurring in a fixed interval of time or space. You will first learn how to read the lambda (λ) parameter and k value, and then implement the Poisson probability formula to calculate the probability of exactly k events occurring in a given interval.

The lab covers the step-by-step process of writing a C program to compute Poisson probabilities, including handling user input, implementing the Poisson probability formula, and printing the calculated probability.

Read λ (lambda) and k

In this step, you'll learn how to read the lambda (λ) parameter and k value for calculating Poisson probabilities in C. The Poisson distribution is a probability distribution that expresses the likelihood of a given number of events occurring in a fixed interval of time or space.

First, let's create a new C file to implement our Poisson probability calculation:

cd ~/project
nano poisson_prob.c

Now, add the following code to read lambda and k values:

#include <stdio.h>
#include <math.h>

int main() {
    double lambda;
    int k;

    printf("Enter lambda (average number of events): ");
    scanf("%lf", &lambda);

    printf("Enter k (number of occurrences): ");
    scanf("%d", &k);

    printf("Lambda (λ): %.2f\n", lambda);
    printf("k: %d\n", k);

    return 0;
}

Example output:

Enter lambda (average number of events): 3.5
Enter k (number of occurrences): 2
Lambda (λ): 3.50
k: 2

Let's break down the code:

  • We use double for lambda to allow decimal values
  • scanf() is used to read user input for lambda and k
  • %lf format specifier is used for double (long float) values
  • %d format specifier is used for integer values
  • We print the entered values to confirm input

Compile the program:

gcc -o poisson_prob poisson_prob.c -lm

Run the program:

./poisson_prob

P(X=k)=e^(-λ)*λ^k/k!

In this step, you'll implement the Poisson probability formula to calculate the probability of exactly k events occurring in a given interval.

Open the previous file to modify the code:

cd ~/project
nano poisson_prob.c

Update the code to include the Poisson probability calculation:

#include <stdio.h>
#include <math.h>

// Function to calculate factorial
double factorial(int n) {
    if (n <= 1) return 1;
    double result = 1;
    for (int i = 2; i <= n; i++) {
        result *= i;
    }
    return result;
}

// Calculate Poisson probability
double poisson_probability(double lambda, int k) {
    double numerator = pow(lambda, k) * exp(-lambda);
    double denominator = factorial(k);
    return numerator / denominator;
}

int main() {
    double lambda;
    int k;

    printf("Enter lambda (average number of events): ");
    scanf("%lf", &lambda);

    printf("Enter k (number of occurrences): ");
    scanf("%d", &k);

    double probability = poisson_probability(lambda, k);

    printf("Lambda (λ): %.2f\n", lambda);
    printf("k: %d\n", k);
    printf("Probability P(X = %d): %.4f\n", k, probability);

    return 0;
}

Compile the program:

gcc -o poisson_prob poisson_prob.c -lm

Example output:

Enter lambda (average number of events): 3.5
Enter k (number of occurrences): 2
Lambda (λ): 3.50
k: 2
Probability P(X = 2): 0.1674

Key points in the code:

  • factorial() function calculates k!
  • poisson_probability() implements the Poisson probability formula
  • pow() calculates λ^k
  • exp() calculates e^(-λ)
  • Result is probability of exactly k events occurring

Run the program:

./poisson_prob

In this final step, you'll enhance the Poisson probability calculation program by adding more detailed probability printing and formatting.

Open the previous file to modify the code:

cd ~/project
nano poisson_prob.c

Update the code to improve probability presentation:

#include <stdio.h>
#include <math.h>

// Function to calculate factorial
double factorial(int n) {
    if (n <= 1) return 1;
    double result = 1;
    for (int i = 2; i <= n; i++) {
        result *= i;
    }
    return result;
}

// Calculate Poisson probability
double poisson_probability(double lambda, int k) {
    double numerator = pow(lambda, k) * exp(-lambda);
    double denominator = factorial(k);
    return numerator / denominator;
}

int main() {
    double lambda;
    int k;

    printf("Poisson Probability Calculator\n");
    printf("------------------------------\n");

    printf("Enter lambda (average number of events): ");
    scanf("%lf", &lambda);

    printf("Enter k (number of occurrences): ");
    scanf("%d", &k);

    double probability = poisson_probability(lambda, k);

    printf("\nCalculation Results:\n");
    printf("Lambda (λ): %.2f\n", lambda);
    printf("k: %d\n", k);
    printf("Probability P(X = %d): %.4f\n", k, probability);
    printf("Percentage: %.2f%%\n", probability * 100);

    return 0;
}

Compile the program:

gcc -o poisson_prob poisson_prob.c -lm

Example output:

Poisson Probability Calculator
------------------------------
Enter lambda (average number of events): 3.5
Enter k (number of occurrences): 2

Calculation Results:
Lambda (λ): 3.50
k: 2
Probability P(X = 2): 0.1674
Percentage: 16.74%

Key improvements:

  • Added a title for the calculator
  • Included percentage representation
  • Improved output formatting
  • More descriptive output sections

Run the program:

./poisson_prob

Summary

In this lab, you learned how to read the lambda (λ) parameter and k value for calculating Poisson probabilities in C. You then implemented the Poisson probability formula to calculate the probability of exactly k events occurring in a given interval. The Poisson distribution is a probability distribution that expresses the likelihood of a given number of events occurring in a fixed interval of time or space. You also learned how to create a factorial function to support the Poisson probability calculation.

The key steps covered in this lab include reading the input values, calculating the Poisson probability using the formula P(X=k)=e^(-λ)*λ^k/k!, and printing the resulting probability.