Question

When analyzing the relationship in non-linear data as a linear association, when should the strategy of ignoring outliers be used?

If ignoring half of the data points allows the remaining data to be represented by a curved line.

If ignoring one or two data points allows the remaining data to be represented by a straight line.

If ignoring half of the data points allows the remaining data to be represented by a straight line.

If ignoring one or two data points allows the remaining data to be represented by a curved line.

Answer 1

The answer is B, or If ignoring one or two data points allows the remaining data to be represented by a straight line.

Explanation:

An outlier is typically one or two points that differ greatly from the rest of the data. If ignoring these outliers contributes to the ability to identify non-linear data as a linear association, then a straight line should still be present regardless of these two points.