Todennäköisyysluku

Todennäköisyysluku, often translated as probability value or p-value, is a fundamental concept in statistical hypothesis testing. It quantifies the probability of obtaining observed, or more extreme, results assuming that the null hypothesis is true. The null hypothesis typically represents a default position, such as stating there is no effect or no difference between groups.

A low p-value indicates that the observed data are unlikely to have occurred if the null hypothesis were correct. Consequently, a small p-value provides evidence against the null hypothesis, leading to its rejection in favor of an alternative hypothesis. Conversely, a high p-value suggests that the observed data are consistent with the null hypothesis, and therefore, there is not enough evidence to reject it.

The threshold for rejecting the null hypothesis is typically set by a significance level, often denoted by alpha (α). Common choices for alpha are 0.05 or 0.01. If the p-value is less than alpha, the result is considered statistically significant. It is important to note that a p-value does not indicate the probability that the null hypothesis is true or false, nor does it measure the size or importance of an effect. It solely assesses the compatibility of the data with the null hypothesis. Misinterpretation of p-values can lead to incorrect conclusions in research.