Uniform random with random() in NumPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does numpy.random.random() do?

It generates a random float number between 0.0 (inclusive) and 1.0 (exclusive), following a uniform distribution.

beginner

How to generate 5 random numbers between 0 and 1 using numpy?

Use numpy.random.random(5) to get an array of 5 random floats between 0 and 1.

intermediate

How can you get random numbers between 10 and 20 using numpy.random.random()?

Multiply the output by 10 and add 10: 10 + 10 * numpy.random.random().

intermediate

What is the difference between numpy.random.random() and numpy.random.uniform()?

random() generates numbers between 0 and 1 only, while uniform(low, high) lets you specify any range.

beginner

Why is uniform random useful in data science?

It helps create random samples, simulate data, and test models with evenly spread values.

What range of values does numpy.random.random() generate?

A 0.0 (inclusive) to 1.0 (exclusive)

B 0 to 1 inclusive

C -1 to 1

D Any float number

numpy.random.random() generates floats from 0.0 up to but not including 1.0.

How do you generate an array of 3 random numbers between 0 and 1?

A numpy.random.uniform(0,3)

B numpy.random.random() * 3

C numpy.random.random(3)

D numpy.random.randint(0,3)

Passing 3 as an argument returns an array of 3 random floats between 0 and 1.

How to get a random number between 5 and 15 using numpy.random.random()?

A numpy.random.uniform(5, 15)

B 5 + 10 * numpy.random.random()

C numpy.random.random() * 15

D numpy.random.random() + 5

Multiply by the range (10) and add the minimum (5) to scale the output.

Which function allows specifying any range for uniform random numbers?

A numpy.random.normal()

B numpy.random.random()

C numpy.random.randint()

D numpy.random.uniform()

numpy.random.uniform(low, high) lets you set the range explicitly.

Why use uniform random numbers in simulations?

A To get evenly spread random values

B To get only integers

C To get normal distribution

D To get fixed values

Uniform random numbers spread evenly across the range, useful for fair sampling.

Explain how to generate random numbers between any two values using numpy.random.random().

Think about multiplying and shifting the 0 to 1 output.

Describe the difference between numpy.random.random() and numpy.random.uniform().

One is fixed range, the other is flexible.