The **decimal random number generator** is a sophisticated tool designed to produce **random numbers** with **decimal places**.

For instance, consider a weather prediction model requiring temperatures accurate to one decimal place. A decimal random number generator might output:

**23.7°C****18.2°C****25.9°C**

## Decimal Random Number Generator

Sample | Random Number |
---|---|

1 | 37.42 |

2 | 85.19 |

3 | 12.76 |

4 | 63.91 |

5 | 49.05 |

6 | 74.88 |

7 | 29.34 |

8 | 91.67 |

9 | 56.23 |

10 | 45.79 |

Mean = (Sum of Random Numbers) / (Total Samples)

Mean = (37.42 + 85.19 + 12.76 + 63.91 + 49.05 + 74.88 + 29.34 + 91.67 + 56.23 + 45.79) / 10

Mean = 474.24 / 10 = **47.42**

For our dataset, let’s calculate it step-by-step:

- Mean:
**47.42** - Squared Differences:
- (37.42 – 47.42)² = 100
- (85.19 – 47.42)² = 1420.56
- (12.76 – 47.42)² = 1195.78
- (63.91 – 47.42)² = 270.78
- (49.05 – 47.42)² = 2.66
- (74.88 – 47.42)² = 738.76
- (29.34 – 47.42)² = 328.68
- (91.67 – 47.42)² = 1936
- (56.23 – 47.42)² = 76
- (45.79 – 47.42)² = 2.66

- Sum of Squared Differences: Sum = 100 + 1420.56 + 1195.78 + 270.78 + 2.66 + 738.76 + 328.68 + 1936 + 76 + 2.66

Sum =**5074** - Variance: Variance = Sum of Squared Differences / Total Samples

Variance = 5074 / 10 =**507.4** - Standard Deviation: Standard Deviation = √Variance

Standard Deviation ≈ √507.4 ≈**22.5**

## Decimal Random Number Formula

The formula for generating decimal random numbers typically involves two key steps:

**Generate a random integer****Scale and shift the result**

If we wanted to generate random numbers between **5.0** and **7.5**, the formula would first create a random fraction, multiply it by the range (**2.5** in this case), and then add the minimum value (**5.0**) to shift the result into the correct range.

## How to Generate Random Numbers with Decimals?

The process typically follows these steps:

**Define the range and precision**: Specify the minimum and maximum values, as well as the number of decimal places required.

**Generate a random base number**: Use the language’s random number function to create a starting point.

**Scale the number**: Adjust the random number to fit within the specified range.

**Apply precision**: Round the result to the desired number of decimal places.

## Sources / Reference URLs

- Python Software Foundation. (2024). random — Generate pseudo-random numbers. https://docs.python.org/3/library/random.html
- National Institute of Standards and Technology. (2023). Random Number Generation. https://csrc.nist.gov/projects/random-bit-generation
- MathWorks. (2024). Generate random numbers – MATLAB & Simulink. https://www.mathworks.com/help/matlab/random-number-generation.html

Related Tools