Random variable generation in SciPy - Mini Project: Build & Apply

Random Variable Generation with SciPy

📖 Scenario: You are working as a data analyst for a small company. You need to simulate some random data to understand how different random variables behave. This will help you prepare reports and visualize data patterns.

🎯 Goal: Learn how to generate random variables using the scipy.stats library. You will create a normal distribution, set parameters, generate random samples, and print the results.

📋 What You'll Learn

Create a normal distribution random variable with mean 5 and standard deviation 2 using scipy.stats.norm.

Set the number of random samples to generate as 10.

Generate 10 random samples from the normal distribution.

Print the generated random samples.

💡 Why This Matters

🌍 Real World

Random variable generation is used in simulations, risk analysis, and modeling real-world uncertain events.

💼 Career

Data scientists and analysts often generate random data to test models, create synthetic datasets, or understand statistical properties.

1

Create a normal distribution random variable

Import scipy.stats and create a normal distribution random variable called normal_rv with mean (loc) 5 and standard deviation (scale) 2 using scipy.stats.norm(loc=5, scale=2).

SciPy

# Import scipy.stats and create normal_rv with mean 5 and std 2
# Your code here

Need a hint?

Use from scipy.stats import norm to import the normal distribution. Then create normal_rv with norm(loc=5, scale=2).

2

Set the number of samples to generate

Create a variable called num_samples and set it to 10 to represent the number of random samples you want to generate.

SciPy

from scipy.stats import norm

normal_rv = norm(loc=5, scale=2)

# Set num_samples to 10
# Your code here

Need a hint?

Just create a variable num_samples and assign it the value 10.

3

Generate random samples

Use the rvs method of normal_rv to generate num_samples random samples. Store the result in a variable called samples.

SciPy

from scipy.stats import norm

normal_rv = norm(loc=5, scale=2)

num_samples = 10

# Generate samples using normal_rv.rvs(num_samples)
# Your code here

Need a hint?

Call normal_rv.rvs(size=num_samples) and assign it to samples.

4

Print the generated samples

Print the variable samples to display the generated random values.

SciPy

from scipy.stats import norm

normal_rv = norm(loc=5, scale=2)

num_samples = 10

samples = normal_rv.rvs(size=num_samples)

# Print the samples
# Your code here

Need a hint?

Use print(samples) to show the generated random numbers.