You will be presented with data produced by different machines.
For each machine, we will show you 27 trials generated by that machine.
Although trials are produced by the same machine, all trials are independent; i.e. previous trials do not affect the next trial.
In every trial:
the machine either makes a sound or doesn’t make a sound.
A machine has lights of multiple colors, including always one red and one blue light. In every trial:
you can see if the red light is on or off;
you can see if the blue light is on or off;
you cannot see the other lights, which could be on or off.
The lights and the sounds may or may not be related to each other.
That is, a trial includes information for lights that can be observed (blue and red) and on whether the machine made a sound or not. It does not provide information for lights that cannot be observed.
Your task in Part 1 is to take summary notes (at most 75 characters) for each machine because in Part 2 you will not have access to the data observed in Part 1.
In Part 2 you will face the same machine again and will make predictions.
In the prediction task, you may be shown partial information about a machine’s trial. This means that you may observe nothing, only the blue light, only the red light or only the sound; or that you may observe two out of the three (that is, you may observe both lights or one light and the sound). Your task will be to predict the elements in the trial that you are not provided with. That is:
If you do not receive information on the red light, you may have to predict it.
If you do not receive information on the blue light, you may have to predict it.
If you do not receive information on the sound, you may have to predict it.
For payment, we will randomly select one of your predictions. If your prediction is correct, we will add {{ C.CURRENCY }}25 to your payoffs.
For payment, we will randomly select one of the machines and pay 0.50{{ C.CURRENCY }} for every correct prediction.
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decide: 1. keep ambiguity of what to predict? (Instructions1.2) 2. incentives. 3. make clear stochasticity? (Instructions1.2)