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Discussion Starter · #1 ·
Hey Flux, we could use you help on interpreting this abstract if you would and always highly appreciated.
thanksI am not good with the P values really.
 

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If you want a bit of mathematical input to understand the statement“while anger reduced this threshold compared with relaxation p<0.05”Suppose you measure the sensitivity threshold of two groups - say one treated in an angry state and another relaxed- to see if there is any effect of anger. You observe that the two averages of the thresholds of the two groups are different. You want to know if the difference is because they were angry or just a “coincidence”i.e they indeed had the thresholds of the relaxed group and it was just due to chance that they had different group averages. If the p-value of the angry group is less than 0.02 that means there is a less than 2% chance that the difference is as large or larger if it was a “coincidence” . It is unlikely that the difference was because they had the thresholds of the relaxed group and the difference was due to chance Naturally if the the p-value is 0.01 there is less than a 1 % chance that the difference between the two averages is as large or larger if it was just due to chance that the averages were different. So it is better to have low p-values.Low p- values in this case that it is more likely the difference was due to anger However do not confuse p-values with the probability that it was due to chance. When you get into probabilities it is a different ball game altogether. . Very simplistically, if you conduct many experiments of angry groups and relaxed groups0.02= No of times relaxed groups had p values<0.02 /No of groups who were actually relaxed with p-values both greater and smaller than or equal to 0.02Probability that the difference in group averages is due to chance ==No of times the relaxed groups had p-values < 0.02 /No of times angry and relaxed groups had p-values <0.02 .
 
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