Random Number Generator

This version of the generator creates a random integer. It can deal with very large integers up to a few thousand digits.

Lower Limit
Upper Limit

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.

Result

71383
419517
496884
3456403
4973295
5957428
6619545
6871134
7028502
7376049
7627052
8197767
8605343
9455337
10701231
10933358
11119496
11476762
11480055
11840306
15556767
15563925
16063172
16218642
16227737
17461078
17502190
19705377
20221332
20703438
21162120
21422277
21501359
22308827
23155767
23806935
26013230
26771121
27347763
28116169
28210025
28545520
28692377
29694336
29856752
30363404
30559670
33357303
36040412
36208121
37726741
38402128
39174507
39803096
40424038
40441505
41136780
42424621
42442516
44270617
45867531
45951500
47204222
49020746
49451530
51147469
51673741
52308633
54058329
54095437
54731656
54738898
55676614
56955287
57731710
57835095
58879344
63853919
64103707
64508485
67260761
69541707
69694385
70626037
72385070
77062668
77344040
78374835
80958479
86412107
88358384
93924865
93925765
94195875
95081434
95492789
95878123
96187167
97545900
98153123
99657545
Lower Limit
Upper Limit
Generate numbers
Type of result to generate?
 

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.

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