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In respect to this, what makes research robust?

In the world of investing, robust is a characteristic describing a model's, test's, or system's ability to perform effectively while its variables or assumptions are altered. For statistics, a test is robust if it still provides insight into a problem despite having its assumptions altered or violated.

Secondly, what does it mean when a sample is robust? Robust statistics, therefore, are any statistics that yield good performance when data is drawn from a wide range of probability distributions that are largely unaffected by outliers or small departures from model assumptions in a given dataset. In other words, a robust statistic is resistant to errors in the results.

Thereof, what is robust method?

Robust statistics are statistics with good performance for data drawn from a wide range of probability distributions, especially for distributions that are not normal. Robust statistical methods have been developed for many common problems, such as estimating location, scale, and regression parameters.

Why is median robust to outliers?

People often believe that because the median is considered a robust measure with respect to outliers that it's also robust to most everything. In fact, it's also considered robust to bias in skewed distributions. As can be seen from the above plot the median (in red) is much more sensitive to the n than the mean.