Timeline for High/low accuracy
Current License: CC BY-SA 4.0
6 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Jan 24, 2019 at 18:41 | vote | accept | Malakias | ||
| Jan 16, 2019 at 15:57 | answer | added | Lawrence | timeline score: 1 | |
| Jan 16, 2019 at 15:56 | comment | added | Malakias | Sorry but no, I am not using accuracy wrongly. Perhaps my example was not the best one but it could be valid though. By accuracy I meant a kind of resolution, or grid, that is used for selecting samples. I do not mean statistical variation! For example, let us have 1000 samples, and then I have a process that selects samples using a grid with intervals of 10 samples. So, the process itself is accurate and repeatable, but it can point only to samples 1, 11, 21, 31, etc. So, I could talk about accuracy of 10 samples, or +/- 5 samples. | |
| Jan 16, 2019 at 15:07 | comment | added | Tuffy | I think your problem is that you are using the word ‘accuracy’ wrongly. Variation in the number of samples used for a test affects not the ACCURACY but the RELIABILITY of the result. The smaller the number samples, the greater the ‘margin for error’. But the ‘error’ is not a matter of accuracy but of how representative the sample is, or how reliable in terms of excluding the possibility that the results were affected by elements irrelevant to the theory. So the RELIABILITY of (say) tests carried out on a new medication increases in direct proportion to the number of samples tested. | |
| Jan 16, 2019 at 13:45 | review | First posts | |||
| Jan 16, 2019 at 15:04 | |||||
| Jan 16, 2019 at 13:42 | history | asked | Malakias | CC BY-SA 4.0 |