Explains the concepts of a hypothesis and a counter-example
Explains that a hypothesis is a conjecture that needs checking and that one counter-example refutes a general statement, whereas examples do not prove it.
Can AI do this?
AI does this well Most of the tested AI models master this. 4 of 4 models in the current benchmark master it.
| Model | Tier | Probability of mastery | Status |
|---|---|---|---|
| gemini-4-argon | Flagship | 100% | Mastered |
| gemini-3.5-flash-lite | Low cost | 100% | Mastered |
| gpt-6-luna | Low cost | 100% | Mastered |
| claude-haiku-5-5 | Low cost | 100% | Mastered |
Mastered means a probability of at least 90% that the model has this knobit, estimated from its graded answers. “Not shown” means the answers do not settle it either way. How the models are tested.
What it looks like in practice
Expected result: An explanation of hypothesis and counter-example
How it is assessed: Tells a hypothesis from a proven statement and states what a counter-example proves
Also known as: Selgitab hüpoteesi ja vastunäite mõistet
Related knobits
Needed for
All knobits of Data modelling.
Source: Copy of k12 knobit K-82024 of the Estonian national curriculum register grok-matemaatika-eesmargid (product k12-curriculum, skills/knobits/k12/grok-matemaatika-eesmargid.yaml), GRÕK lisa 5, lai matemaatika, õpiväljund 4; fingerprint translated from Estonian