Question

Write statements that assign random integers to the variable $n$ in the following ranges: a. $1\le n\le 2$ b. $1\le n\le 100$ c. $0\le n\le 9$ d. $1000\le n\le 1112$ e. $1\le n\le 1$ f. $3\le n\le 11$

Short answer

Use `random.randint(1, 2)`, `random.randint(1, 100)`, `random.randint(0, 9)`, `random.randint(1000, 1112)`, `random.randint(1, 1)`, `random.randint(3, 11)`.

Step-by-step solution

Understanding Libraries

For generating random integers in Python, we'll use the `random` library. This library has a function called `randint(a, b)` that returns a random integer N such that $a\le N\le b$. We'll apply this function to generate the required numbers.

Generating Random Integer for 1 ≤ n ≤ 2

To generate a random integer $n$ such that $1\le n\le 2$, we use `random.randint(1, 2)`. This will include the numbers 1 and 2.

Generating Random Integer for 1 ≤ n ≤ 100

For the range $1\le n\le 100$, we write `random.randint(1, 100)` to include any integer from 1 to 100.

Generating Random Integer for 0 ≤ n ≤ 9

In this step, for generating an integer $n$ that is between 0 and 9 inclusive, use `random.randint(0, 9)`.

Generating Random Integer for 1000 ≤ n ≤ 1112

Here, the random integer $n$ between 1000 and 1112 can be obtained using `random.randint(1000, 1112)`.

Generating Random Integer for 1 ≤ n ≤ 1

Since the range has the same start and end value, `random.randint(1, 1)` will always return the number 1.

Generating Random Integer for 3 ≤ n ≤ 11

Finally, for the range from 3 to 11 inclusive, use `random.randint(3, 11)`.

Key concepts

Python programming

Python is a popular and versatile programming language known for its simplicity and readability. It has a wide range of applications including web development, data analysis, artificial intelligence, and more. One of the key features that make Python popular among developers is its extensive library support.
Python's syntax is designed to be intuitive, often mirroring how humans think. This means you can express concepts without writing cumbersome code.

• Python supports multiple programming paradigms including procedural, object-oriented, and functional programming.
• It is an interpreted language, meaning Python code is executed line by line which simplifies debugging.
• Python is platform-independent and can run on various operating systems like Windows, Linux, and macOS.

Whether you are developing a small script or a large-scale application, Python offers modules and packages to speed up the coding process and enhance functionality.

ranges in programming

In programming, a range is often used to represent a sequence or a span of numbers. Understanding how to properly declare and use ranges is crucial for tasks like iteration, where you repeat actions for a set of values.
A simple example in Python would be using `range()` to work with sequences. When creating a range of numbers, you define a start point, an endpoint, and an optional step value.

• The `range()` function generates a sequence of numbers, not including the last number you specify.
• It is commonly used with loops to perform an action a set number of times.
• Ranges can encompass different intervals; they can be open-ended or closed, depending on whether the endpoint is included.

Using ranges allows for efficient looping and indexing, which saves both memory and computing time by not generating the numbers in a sequence all at once but as needed.

integer generation

Integer generation involves creating whole numbers within a specified range. In various applications like simulations or game development, you often need random integers.
In Python, generating integers is straightforward, thanks to built-in functions. One of the primary functions used for this purpose is `randint()` from the `random` library.

• `randint(a, b)` returns a random integer `N` such that the values are spread across a uniform distribution.
• The function accommodates both endpoints (a and b) in the generated numbers.

Generating random integers can help in testing, sampling, and any case where uncertainty or variability is simulated for real-world conditions.

random library

The random library in Python is a powerful and flexible tool for introducing randomness into your programs. Whether you want to shuffle a list, generate random numbers, or simulate random phenomena, the random library has functions to help.
Some of the most commonly used functions in the random library include:

• `random.randint(a, b)`: Returns a random integer N such that `a <= N <= b`.
• `random.choice(sequence)`: Returns a random element from a non-empty sequence like a list or a string.
• `random.random()`: Generates a random float number between 0.0 to 1.0.

Understanding how to use the random library efficiently can greatly assist in developing unpredictable or non-repeatable program behavior necessary for games, simulations, and randomized testing.