Contents
Do P values range from 0 to 1?
Being a probability, P can take any value between 0 and 1. Values close to 0 indicate that the observed difference is unlikely to be due to chance, whereas a P value close to 1 suggests no difference between the groups other than due to chance.
Can the p-value of a test be greater than 1?
A p-value tells you the probability of having a result that is equal to or greater than the result you achieved under your specific hypothesis. It is a probability and, as a probability, it ranges from 0-1.0 and cannot exceed one.
What does p-value over 1 mean?
The level of statistical significance is often expressed as a p-value between 0 and 1. The smaller the p-value, the stronger the evidence that you should reject the null hypothesis. A p-value less than 0.05 (typically ≤ 0.05) is statistically significant.
When is the p-value of a test really 1?
In some cases the p-value is not truly 1 but this is just an artifact of the statistical software (for example, when SPSS does Bonferroni correction, it sometimes reports p-values of 1, but this is not accurate). The only time a p-value is really 1 is in the situation Jochen described, i.e., when the test statistic is 0.
Can a p-value be 1.0 in SPS?
The p-value can be exactly 1 in sps, if you use bonferroni correction. To avoid alpha-error cummulation when doing multiple pairwise comparisons sps multiplies the p-values by the number of comparisons. For example: If you compare 10 pairs every p-value >= 0,100 will be corrected to 1.
Can a p-value be 1.0 in their thesis?
In your case, the two groups (whatever they are) don’t have the same values so the p-value cannot really be 1: there clearly is some small difference between the groups, and thus some nonzero chance that another sample under a null hypothesis of 0 could get an even smaller difference. Can people report P-value = 1 in their thesis?
Is it good to have a low p value?
Low p-values are sexy. They represent exciting findings and can help you get articles published. However, you might be surprised to learn that higher p-values, the ones that are not statistically significant, are also valuable.