Definitions for p-value
p-value

P-value
In null-hypothesis significance testing, the p-value is the probability of obtaining test results at least as extreme as the result actually observed, under the assumption that the null hypothesis is correct. A very small p-value means that such an extreme observed outcome would be very unlikely under the null hypothesis. Reporting p-values of statistical tests is common practice in academic publications of many quantitative fields. Since the precise meaning of p-value is hard to grasp, misuse is widespread and has been a major topic in metascience.

p-value
In statistical significance testing, the p-value is the probability of obtaining a test statistic at least as extreme as the one that was actually observed, assuming that the null hypothesis is true. A researcher will often "reject the null hypothesis" when the p-value turns out to be less than a certain significance level, often 0.05 or 0.01. Such a result indicates that the observed result would be highly unlikely under the null hypothesis. Many common statistical tests, such as chi-squared tests or Student's t-test, produce test statistics which can be interpreted using p-values. In a statistical test, the p-value is the probability of getting the same value for a model built around two hypotheses, one is the "neutral" hypothesis, the other is the hypothesis under testing. If this p-value is less than or equal to the threshold value previously set, one rejects the neutral hypothesis and accepts the test hypothesis as valid . In general, considering the following thresholds: : very strong presumption against neutral hypothesis : very strong presumption against neutral hypothesis : strong presumption against neutral hypothesis : low presumption against neutral hypothesis

Chaldean Numerology
The numerical value of p-value in Chaldean Numerology is: 2
Pythagorean Numerology
The numerical value of p-value in Pythagorean Numerology is: 5

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