Finding outlier values for non-normally distributed data

I have univariate data (38 is the sample size).The distribution is certainly not normal. How can I find the outliers? I used z-score but am not getting a desired result.

• One of many definitions of outliers is that they are values surprising on the current model of the data. As you are clear that a normal distribution is an implausible model, you should assess your data in the context of a better model (lognormal? gamma? we can't tell). There is no canonical, universal definition of outliers that makes them unambiguously identifiable. Conversely, $z$ scores tell you little or nothing here as they are based on mean and SD which may well be unhelpful summaries any way. For better advice, post your data. For more advice, see several threads here on outliers. – Nick Cox May 20 '16 at 14:12
• Compare stats.stackexchange.com/questions/78063/… for the origin of a similar statement. – Nick Cox May 20 '16 at 14:13
• Thanks for your reply Nick Cox. Well here are my data: 2668, 159, 1167, 765, 491, 979, 1216, 403, 1459, 980, 271, 591, 215, 296, 871, 523, 1105, 698, 852, 409, 493, 252, 818, 743, 731, 439, 488, 306, 546, 1170, 201, 350, 1963, 653, 597, 377, 345, 758. Do I need non parametric tests? If so,what tests should i use? – user3798510 May 20 '16 at 14:45
• How could there be a non-parametric test for an outlier? – Nick Cox May 20 '16 at 14:50
• well..by that i meant if I should consider detecting outliers without assuming that the data follows any sort of distribution.What does the data suggest? – user3798510 May 20 '16 at 14:55