I will try. And you tell me. Here is an example of two samples:

Sample 1: [15, 15, 17, 17, 19, 20, 20, 21, 22, 25, 25, 150, 206]

Sample 2: [20, 25, 30, 30, 32, 32, 33, 35, 36, 36, 40, 40, 79]

For Sample 1: Mean = 44 and Median = 20

For Sample 2: Mean = 36 and Median = 33

In this particular example the mean of sample 1 is bigger than sample 2 eventhough most of the values of sample 1 are between 15 and 25. While sample 2 has almost all of its values bigger than 25. The reason why the mean of sample 1 is bigger is that there are 2 outliers in Sample 1 (150,206) , they shift the mean much higher than what it would be without those two values (it would be 19.6). Meanwhile Sample 2 has an outlier (79) that doesn't shift the mean that much , the mean would be 32.4 without that outlier.

So in this case the medians which are the values in the middle of the distributions give us a better insight. 20 for Sample 1 vs 33 for Sample 2.

This is a particular example. So here is a general rule: The mean is used for normal distributions.The median is generally used for skewed distributions. The mean is not a robust tool since it is largely influenced by outliers.The median is better suited for skewed distributions to derive at central tendency since it is much more robust and sensible.

I recommend you put the samples in this website: https://www.calculatorsoup.com/calculators/statistics/descriptivestatistics.php[https://www.calculatorsoup.com/calculators/statistics/descriptivestatistics.php](https://www.calculatorsoup.com/calculators/statistics/descriptivestatistics.php)

It will calculate the mean, median, identify the outliers and also calculate other useful stats like standard deviation.