What Role Does Gaussian Distribution Play in Error Analysis?
In experimental nanotechnology, measurements are often subject to various sources of error. Gaussian distribution is essential for error analysis because it allows researchers to quantify the uncertainty and variability in their data. By assuming that measurement errors follow a normal distribution, it becomes possible to apply statistical methods to estimate confidence intervals and make more accurate predictions.
