{"id":216340,"date":"2024-01-07T16:28:03","date_gmt":"2024-01-07T16:28:03","guid":{"rendered":"https:\/\/namso-gen.co\/blog\/what-p-value-makes-something-statistically-significant\/"},"modified":"2024-01-07T16:28:03","modified_gmt":"2024-01-07T16:28:03","slug":"what-p-value-makes-something-statistically-significant","status":"publish","type":"post","link":"https:\/\/namso-gen.co\/blog\/what-p-value-makes-something-statistically-significant\/","title":{"rendered":"What P value makes something statistically significant?"},"content":{"rendered":"

When analyzing the results of a statistical experiment, researchers often rely on the concept of statistical significance to determine whether the observed results are likely due to chance or if they represent a true effect. The most common measure used to evaluate statistical significance is the p-value. But what exactly is a p-value, and what threshold should be used to determine whether something is statistically significant?<\/p>\n

To put it simply, a p-value is a probability that measures the strength of evidence against the null hypothesis – the assumption that there is no effect or relationship between variables. It quantifies how likely it is to observe the obtained data, or data more extreme, under the null hypothesis. In other words, a smaller p-value indicates stronger evidence against the null hypothesis and suggests that the observed effect is unlikely to be due to chance alone.<\/p>\n

Now, to address the question directly: the **p-value that is commonly used to determine statistical significance is typically less than or equal to 0.05**. This threshold value of 0.05 means that if the obtained p-value is less than 0.05, it is considered statistically significant and provides evidence against the null hypothesis.<\/p>\n

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