{"id":250428,"date":"2024-05-22T16:54:26","date_gmt":"2024-05-22T16:54:26","guid":{"rendered":"https:\/\/namso-gen.co\/blog\/?p=250428"},"modified":"2024-05-22T16:54:26","modified_gmt":"2024-05-22T16:54:26","slug":"what-p-value-accepts-the-null-hypothesis-2","status":"publish","type":"post","link":"https:\/\/namso-gen.co\/blog\/what-p-value-accepts-the-null-hypothesis-2\/","title":{"rendered":"What P value accepts the null hypothesis?"},"content":{"rendered":"

When conducting statistical hypothesis testing, the p-value plays a crucial role in determining whether to accept or reject the null hypothesis. The p-value represents the probability of obtaining results as extreme or more extreme than the observed data, assuming that the null hypothesis is true. It is customary to compare the p-value with a pre-defined significance level, often denoted as alpha (\u03b1), to make a decision. If the p-value is less than or equal to the significance level, we reject the null hypothesis. Conversely, if the p-value is greater than the significance level, we fail to reject the null hypothesis. But what specific p-value accepts the null hypothesis? Let’s explore further.<\/p>\n

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