There are many definitions of randomness - some good and some less ideal! In the main module, we will be looking at the no-pattern definition and the equiprobability definition. Here, you will find a few other examples.
As an exercise, we recommend discussing some of the pro’s and con’s to each of these definitions with your classmates.
Which one do you prefer and why?
| Definition Label | Definition | Reference | |
|---|---|---|---|
| Equiprobability Definition | Randomness is where each observation is equally likely to be selected. | Batanero et al. (2016) | |
| No-Pattern Definition | Randomness is where a sequence lacks a discernible pattern. | Gougis et al. (2017) | |
| Subjective Definition | Randomness is dependent on a person’s knowledge. | Batanero et al. (2016) | |
| Zero-Correlation Definition | Randomness is where the correlation between pairs of adjacent observations is zero. | Nickerson (2002) | |
| Algorithmic Definition | Randomness is where no algorithm can predict future observations of a sequence. | Batanero et al. (2016) | |
| Compressibility Definition | Randomness is where a sequence cannot be compressed or compacted into a shorter form. | Chaitin (1975) | |
| Predictability Definition I | Randomness is where the outcome cannot be predicted even though the probability of each observation is fixed. | New Zealand Ministry of Education (2012) | |
| Predictability Definition II | Randomness is where it is impossible to predict when an observation will occur | Bennett (2011) |
This site has been created as part of my PhD thesis on perceptions of randomness. I am always keen for feedback, so please email me any thoughts you have via amy.renelle@auckland.ac.nz. Thank you to my supervisors, Dr. Stephanie Budgett and Dr. Rhys Jones, for their guidance throughout my project. I would also like to thank Anna Fergusson for her help inspiring and creating this website. You can find the references for this site here.