P-value

Information

• P-value is a statistical measure that helps to determine the significance of a result in a hypothesis test.
• It represents the probability of obtaining an observation or a more extreme observation, assuming the null hypothesis is true.
• The null hypothesis is the hypothesis that there is no significant difference between two groups or variables.
• The smaller the p-value, the more evidence we have against the null hypothesis and the stronger the evidence in favor of the alternative hypothesis.
• The significance level, commonly set at 0.05, is the threshold at which we reject the null hypothesis. If the p-value is less than the significance level, we reject the null hypothesis and accept the alternative hypothesis.
• The p-value is often misinterpreted as the probability of the null hypothesis being true, which is incorrect.
• P-values should be used in conjunction with effect sizes, confidence intervals, and other statistical measures to draw meaningful conclusions from data.