# Is the p-value mean?

**the probability, for a given statistical model that, when the null hypothesis is true, the statistical summary would be equal to or more extreme than the actual observed results**[2].

## Is p-value related to mean?

If the test statistic is far from the mean of the null distribution, then the p-value will be small, showing that the test statistic is not likely to have occurred under the null hypothesis.## What does p-value of 0.05 mean?

P > 0.05 is the probability that the null hypothesis is true. 1 minus the P value is the probability that the alternative hypothesis is true. A statistically significant test result (P ≤ 0.05) means that the test hypothesis is false or should be rejected. A P value greater than 0.05 means that no effect was observed.## Is the p-value the mean difference?

The p-value is the probability that the difference between the sample means is at least as large as what has been observed, under the assumption that the population means are equal.## What does high p-value mean?

High p-values indicate that your evidence is not strong enough to suggest an effect exists in the population. An effect might exist but it's possible that the effect size is too small, the sample size is too small, or there is too much variability for the hypothesis test to detect it.## What Is A P-Value? - Clearly Explained

## Is a higher or lower p-value better?

The p-value can be perceived as an oracle that judges our results. If the p-value is 0.05 or lower, the result is trumpeted as significant, but if it is higher than 0.05, the result is non-significant and tends to be passed over in silence.## How do you interpret the p-value in a sentence?

A P-value is a number between 0 and 1 and in literature, it is usually interpreted in the following way: A small P-value (<0.05) indicates strong evidence against the null hypothesis. A large P-value (>0.05) indicates weak evidence against the null hypothesis.## What is the relationship between p-value and sample mean?

A P value is also affected by sample size and the magnitude of effect. Generally the larger the sample size, the more likely a study will find a significant relationship if one exists. As the sample size increases the impact of random error is reduced.## How do you explain p-value to non statisticians?

A p-value is a probability, a number between 0 and 1, calculated after running a statistical test on data. A small p-value (< 0.05 in general) means that the observed results are so unusual assuming that they were due to chance only.## What does the p-value signify in a hypothesis test?

The P value, or calculated probability, is the probability of finding the observed, or more extreme, results when the null hypothesis (H_{0}) of a study question is true – the definition of 'extreme' depends on how the hypothesis is being tested.