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Apr 14, 2019 at 13:42 answer added Sal Mangiafico timeline score: 1
Apr 10, 2019 at 15:11 answer added AdamO timeline score: 0
Apr 10, 2019 at 14:44 comment added AdamO @GermanDemidov I disagree with your points here. One can easily calibrate the T-test when the distribution is small and non-normal, even multimodal (use simulation). It's easy to show the type-1 error rate is conserved and that the test has some power. At any rate, a jackknife could be recommended as an alternative. The important point is coding LLD values as 0 when they are positively valued.
Apr 10, 2019 at 14:26 comment added whuber You should not treat the BDL values as zeros. This introduces two biases: first, it (obviously) biases the mean downwards. More subtly, it biases the standard deviation upwards. The amount of bias depends on the reporting limits. See Dennis Helsel's book Nondetections and data analysis. Nevertheless, unless your reporting limits are all substantially greater than 110 mg/Kg, there's little question that these data are from a population with mean less than 110.
S Apr 10, 2019 at 14:15 history edited Bert Nyarenchi CC BY-SA 4.0
Made it reproducible and shorter
Apr 10, 2019 at 14:08 review Suggested edits
S Apr 10, 2019 at 14:15
Apr 10, 2019 at 13:53 answer added user213325 timeline score: 1
Apr 10, 2019 at 13:10 review First posts
Apr 10, 2019 at 13:20
Apr 10, 2019 at 13:09 comment added German Demidov I would say no - you have 0-inflated values and your sample size of 10 is too small. You can take (number of values smaller than 110, number of values bigger than 110) and make a sign test - if the null hypothesis that the mean is equal to 110 is true, you should have approx equal number of values that exceed the mean and that are below (I guess it is called not sign test but Binomial).
Apr 10, 2019 at 13:06 history asked Bert Nyarenchi CC BY-SA 4.0