Yes. When the data is perfectly described by the resticted model, the probability to get data that is less well described is 1. For instance, if the sample means in two groups are identical, the p-values of a t-test is 1.
What is the maximum p-value?
A small p-value (typically ≤ 0.05 ) indicates strong evidence against the null hypothesis, so you reject the null hypothesis. A large p-value (> 0.05) indicates weak evidence against the null hypothesis, so you fail to reject the null hypothesis. ... Always report the p-value so your readers can draw their own conclusions.
Can P value be more 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 .
Can you have multiple p-values?
A P value of 0.05 means that there’s a 5% chance of getting your observed result, if the null hypothesis were true. ... In that case, you’d have about 5 statistically significant results, all of which were false positives.
Is it possible to have a value for the probability to be greater than 1?
Probability of an event cannot exceed 1 . probability of any thing will lie between 0 to 1.
What if p-value is 0?
P value 0.000 means the null hypothesis is true . ... Anyway, if your software displays a p values of 0, it means the null hypothesis is rejected and your test is statistically significant (for example the differences between your groups are significant).
What does p-value tell you?
A p-value is a measure of the probability that an observed difference could have occurred just by random chance . The lower the p-value, the greater the statistical significance of the observed difference. P-value can be used as an alternative to or in addition to pre-selected confidence levels for hypothesis testing.
When should the p-value be adjusted?
A p-value adjustment is necessary when one performs multiple comparisons or multiple testing in a more general sense: performing multiple tests of significance where only one significant result will lead to the rejection of an overall hypothesis.
What is adjusted p-value vs p-value?
You can set the significance level to any probability you want. The adjusted P value is the smallest familywise significance level at which a particular comparison will be declared statistically significant as part of the multiple comparison testing. ... Each comparison will have a unique adjusted P value.
Why is my p-value higher than 1?
Explanation: 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. ... A p-value higher than one would mean a probability greater than 100% and this can’t occur .
Why does probability have to be between 0 and 1?
The probability of an event will not be less than 0 . This is because 0 is impossible (sure that something will not happen). The probability of an event will not be more than 1. This is because 1 is certain that something will happen.
Can a CDF be greater than 1?
Not only the probability density can go greater than 1 , it can assume even bigger values (the biggest one is noted here) as long as the area under it is 1. Consider a probability density function of some continuous distribution.
Is p-value 0.1 Significant?
Significance Levels. The significance level for a given hypothesis test is a value for which a P -value less than or equal to is considered statistically significant . Typical values for are 0.1, 0.05, and 0.01. These values correspond to the probability of observing such an extreme value by chance.
Is P 0.001 statistically significant?
Most authors refer to statistically significant as P < 0.05 and statistically highly significant as P < 0.001 (less than one in a thousand chance of being wrong).
Why is my p-value so low?
A very small P-value indicates that the null hypothesis is very incompatible with the data that have been collected . ... A small P-value could be simply due to a very large sample size regardless of the effect size. A P-value>0.05 does not mean that no effect was observed, or that the effect size was small.
