Probability structure of probabilistic learning (weather prediction) task
| Cue pattern | Cue | p(cue combination) | p(outcome) | |||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | |||
| 1 | 0 | 0 | 0 | 1 | 0.133 | 0.150 |
| 2 | 0 | 0 | 1 | 0 | 0.087 | 0.385 |
| 3 | 0 | 0 | 1 | 1 | 0.080 | 0.083 |
| 4 | 0 | 1 | 0 | 0 | 0.087 | 0.615 |
| 5 | 0 | 1 | 0 | 1 | 0.067 | 0.200 |
| 6 | 0 | 1 | 1 | 0 | 0.040 | 0.500 |
| 7 | 0 | 1 | 1 | 1 | 0.047 | 0.143 |
| 8 | 1 | 0 | 0 | 0 | 0.133 | 0.850 |
| 9 | 1 | 0 | 0 | 1 | 0.067 | 0.500 |
| 10 | 1 | 0 | 1 | 0 | 0.067 | 0.800 |
| 11 | 1 | 0 | 1 | 1 | 0.033 | 0.400 |
| 12 | 1 | 1 | 0 | 0 | 0.080 | 0.917 |
| 13 | 1 | 1 | 0 | 1 | 0.033 | 0.600 |
| 14 | 1 | 1 | 1 | 0 | 0.047 | 0.857 |
For any given trial, 1 of the 14 possible cue pattern combinations displayed above appeared on the computer screen with a probability indicated as p(cue combination). As shown above, the probability of the cue combinations to predict ″sunshine″ (outcome 1) was set at p(outcome). Conversely, the probability of the above cue combinations to predict ″rain″ (or outcome 2) was equal to 1 − p.