# Random Number Generator

Welcome to our random integer generator! This powerful tool allows you to generate random integers, even with incredibly large values spanning up to a few thousand digits. Whether you need a random integer for mathematical calculations, cryptography, or any other purpose, our generator can handle it with ease. Enjoy the flexibility and versatility of generating random integers of any size with just a few clicks.

## Comprehensive Version

This version of the generator can create one or many random integers or decimals. It can deal with very large numbers with up to 999 digits of precision.

### What is Random Number Generator ?

A random number is a number chosen from a pool of limited or unlimited numbers that has no discernible pattern for prediction. The pool of numbers is almost always independent from each other. However, the pool of numbers may follow a specific distribution. For example, the height of the students in a school tends to follow a normal distribution around the median height. If the height of a student is picked at random, the picked number has a higher chance to be closer to the median height than being classified as very tall or very short. The random number generators above assume that the numbers generated are independent of each other, and will be evenly spread across the whole range of possible values.

A random number generator, like the ones above, is a device that can generate one or many random numbers within a defined scope. Random number generators can be hardware based or pseudo-random number generators. Hardware based random-number generators can involve the use of a dice, a coin for flipping, or many other devices.

A pseudo-random number generator is an algorithm for generating a sequence of numbers whose properties approximate the properties of sequences of random numbers. Computer based random number generators are almost always pseudo-random number generators. Yet, the numbers generated by pseudo-random number generators are not truly random. Likewise, our generators above are also pseudo-random number generators. The random numbers generated are sufficient for most applications yet they should not be used for cryptographic purposes. True random numbers are based on physical phenomena such as atmospheric noise, thermal noise, and other quantum phenomena. Methods that generate true random numbers also involve compensating for potential biases caused by the measurement process.

### Random Number Generator Example

Data Input | Description | Example |
---|---|---|

Minimum Value | The minimum value of the range for generating random numbers | 1 |

Maximum Value | The maximum value of the range for generating random numbers | 100 |

Quantity | The number of random numbers to generate | 5 |

Data Output | Description | Example |
---|---|---|

Random Numbers | The generated random numbers within the specified range and quantity | 34, 78, 12, 45, 99 |

In this example, the user would input the minimum and maximum values to define the range within which the random numbers should be generated. Additionally, the user can specify the quantity of random numbers they want to generate. The Random Number Generator would then generate the specified quantity of random numbers within the given range.

Please note that this is just an example table, and the specific implementation of the Random Number Generator may vary based on the programming or algorithm used.