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Due to random deployment of nodes, sometimes the deployment is worse for a given experiment.
Users are randomly assigned to two or more groups for a given experiment.
Even if parameters are theoretically identifiable, they may be poorly estimable for a given experiment.
In summary, choosing an appropriate network for a given experiment involves trade-offs and is an iterative process.
Deciding on the exact form of a Wilson network model for a given experiment is not at this stage algorithmic.
The stimulus timing for a given experiment should therefore be generated with the required detectability and estimation accuracy.
The exact procedure for a given experiment should be tailored to the specific needs of the empirical question studied.
To construct a Wilson network for a given experiment, we must assume which attributes and which levels appropriately define a pattern.
Some important aspects of edX AB experiments are as follows: Users are randomly assigned to two or more groups for a given experiment.
This structure of levels gives the needed flexibility for organising authorisation, and hides data that are not relevant for a given experiment.
Experimental conclusions are predominantly associated with application of the herder material and usability for a given experiment scale to make response decisions.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com