# AB Test Design with Outliers ðŸ¤¯ â€” Solutions Part I

Two weeks ago, we discussed the issue of outliers in the context of designing your A/B test. If you need a quick reminder, you can find the relevant post here:

# AB Test Design with Outliers ðŸ¤¯

# So what are your options?

There are several options you could choose when dealing with outliers.

The simplest solution is to use the **trimmed-mean t-test**.

Essentially this is a t-test using the trimmed means of each sample as the means and theWinsorized(trimmed) variances as the variances.

The idea behind this approach is straightforward: if you have data points that are either too big or too small, you throw them away.

Of course, if you have a strong statistics background, you might question the validity of this approachâ€¦