I’m stuck on a Statistics question and need an explanation.
Answer the question:
Suppose the sample size of an observation study could be expanded to be infinitely large. What sources of error would be eliminated. What sources of error would remain unaffected?
Respond to the answer:
Error is characterized as the variation between the true and recorded value of a measurement. There are several sources of error in gathering epidemiological studies and can be identified as random or systematic. Random error is otherwise called changeability or arbitrary variety. Systematic error alludes to anomalies that are not because of chance alone.
In an observation study that was expanded to infinitely large, the random error would be removed however not the systematic error. Hypothetically, if all unknown variables could be distinguished, it is conceivable to eliminate confounding, the control of which might be prevented in customary studies by the absence of sufficient data. Selection bias and information bias would be unaffected by having infinite data in a case-control study. In an infinitely large randomized trial there would be no random error and no confounding, because the randomized groups would be evenly balanced. Systematic errors such as ascertainment bias, if present, would not be affected by the infinite size.
Penn State. (2018). Lesson 4: Bias and Random Error. Retrieved from https://online.stat.psu.edu/stat509/node/26/
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