Why are robust statistics important in data analysis?

Why are robust statistics important in data analysis?

Robust statistics are crucial because they provide reliable results even when data contains outliers or is not normally distributed.

Can you give an example of a robust statistical method?

Sure! The median is a robust statistic because it is not affected by extreme values, unlike the mean.

How do robust statistics improve decision-making?

They enhance decision-making by ensuring that conclusions drawn from data are valid and not skewed by anomalies.

What are some common robust statistical techniques?

Common techniques include trimmed means, Winsorized means, and robust regression methods.

When should I use robust statistics instead of traditional methods?

Use robust statistics when your data may contain outliers or when the underlying assumptions of traditional methods are violated.