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Experimentalists need to understand how many samples they need to reproduce results for a future experiment. Typically, people will run pilot studies with a few samples, and then assess variation, and use that variation to run a real larger study. But more samples = money
Subtasks
- Scope the sample size UI and sample size server to understand how to best not repeat bad patterns.
- Look into this example tutorial on how to use the futureExperimentSimulation function and inspect its inputs and outputs
- Compare the input and output of the futureExperimentSimulation function with the designSampleSize and designSampleSizePlots functions and verify where inputs and outputs differ
- Make outputs of the futureExperimentSimulation function align with designSampleSize as much as possible.
- If dose response curve option is enabled, then call the futureExperimentSimulation function in the backend and update dynamically the user options.
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