An outlier is typically described as a data point or observation in a collection of data points that is "very distant" from the other points and thus could be due to, for example, some fault in the measurement procedure. Identification and removal of outliers is often controversial, and is typically "more acceptable" in situations where the model used to describe the data is well known and well accepted.
This tutorial will show you how to:
The procedure described in this tutorial is also applicable to other fitting tools such as Polynomial and Nonlinear Fitting
At this point, we can mask data using either the worksheet or the graph. We will start by demonstrating how to mask plotted data from the worksheet.
To mask data in the graph: