tag:blogger.com,1999:blog-7310946608587805029.post8428944678639893565..comments2024-03-13T01:48:29.943-04:00Comments on Unbiased Research: Is statistical testing worth it?TJ Murphyhttp://www.blogger.com/profile/17292359594683490598noreply@blogger.comBlogger2125tag:blogger.com,1999:blog-7310946608587805029.post-24934227881088057492016-04-23T00:46:57.763-04:002016-04-23T00:46:57.763-04:00I totally that statistically significant results c...I totally that statistically significant results can be scientifically irrelevant. And I would say that sometime scientifically important result might not have statistical significance. <br /><br />At least I was in this kind of situation once. In bacterial growth inhibition assay of extract treatment, we can regard the data in two ways: percentage inhibition of bacterial growth at a certain concentration, or the extract concentration that reaches 50% percent inhibition. We can use ANOVA or t tests on the percentage inhibition data to show statistical significance in difference. But the extract concentration is the lower the better. But the effectiveness of extracts is hard to evaluate if you are testing multiple strain; it is when you got low concentration for one strain but might have not much percentage inhibition towards another.<br /><br />I'm not sure if I explain my trouble well, but I just want to second your point that we have to make the judge of science after statistical test.Anonymoushttps://www.blogger.com/profile/08634324161272639136noreply@blogger.comtag:blogger.com,1999:blog-7310946608587805029.post-90845329686346428012016-04-19T10:55:32.217-04:002016-04-19T10:55:32.217-04:00I think p values, despite frequently being misused...I think p values, despite frequently being misused, can still be a useful statistical parameter. However, I don't think P values alone are very informative. When evaluating a scientific result, we should ask ourselves the following:<br />1) How likely was it this result was obtained by chance if the null is true?<br />2) How big is the effect? I'm not sure I care if my favorite food increases my chance of getting cancer by 0.000000000000000000000000000001%. It's still valuable scientific knowledge to have, because it may lead us to important biological mechanisms, but how we communicate that result should be different than if it was a 10% increase.<br />3) Is the study adequately powered? Is an outlier driving a major result? I don't really care if it's statistically significant if it's underpowered and removing a single outlier data point kills your significance. Design a better study.<br /><br />More directly to your point, I think statistical testing is good because even if it can be abused, it does give us a rigorous way of looking at data. Humans are way too good at seeing patterns in noise: Without statistical testing of some kind, we will become more biased, not less.Anonymoushttps://www.blogger.com/profile/11397619950259129429noreply@blogger.com