{"id":222105,"date":"2025-01-31T11:34:51","date_gmt":"2025-01-31T11:34:51","guid":{"rendered":"https:\/\/namso-gen.co\/blog\/what-is-critical-p-value\/"},"modified":"2025-01-31T11:34:51","modified_gmt":"2025-01-31T11:34:51","slug":"what-is-critical-p-value","status":"publish","type":"post","link":"https:\/\/namso-gen.co\/blog\/what-is-critical-p-value\/","title":{"rendered":"What is critical P value?"},"content":{"rendered":"

When conducting statistical analysis, researchers often rely on a measure called the p-value to determine the significance of their results. The p-value represents the probability of obtaining results as extreme as the ones observed, assuming that the null hypothesis is true. In simpler terms, it helps determine whether the observed findings are due to chance or if they are statistically significant. To interpret the p-value, researchers compare it to a predetermined value known as the critical p-value.<\/p>\n

The **critical p-value** is a pre-established threshold that determines when the results of a statistical test can be considered statistically significant. It is usually denoted by the Greek letter alpha (\u03b1). The commonly used significance level for alpha is 0.05, which corresponds to a 5% chance of falsely rejecting the null hypothesis. When a p-value is less than the critical p-value, the null hypothesis is rejected, suggesting that the results are statistically significant and not due to random chance.<\/p>\n

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