{"id":211361,"date":"2024-03-15T08:19:06","date_gmt":"2024-03-15T08:19:06","guid":{"rendered":"https:\/\/namso-gen.co\/blog\/is-it-better-for-our-p-value-to-be-higher\/"},"modified":"2024-03-15T08:19:06","modified_gmt":"2024-03-15T08:19:06","slug":"is-it-better-for-our-p-value-to-be-higher","status":"publish","type":"post","link":"https:\/\/namso-gen.co\/blog\/is-it-better-for-our-p-value-to-be-higher\/","title":{"rendered":"Is it better for our p-value to be higher?"},"content":{"rendered":"

When conducting statistical tests, the p-value is a key factor in determining the significance of our findings. But is it better for our p-value to be higher? The short answer is **no,** it is not better for our p-value to be higher. A lower p-value indicates stronger evidence against the null hypothesis, suggesting that the results are statistically significant.<\/p>\n

A p-value is a measure that helps us determine the strength of the evidence against the null hypothesis. It represents the probability of obtaining results as extreme as the ones observed in the data if the null hypothesis were true. In statistical hypothesis testing, a common threshold for significance is a p-value of 0.05. <\/p>\n

If the p-value is less than 0.05, we reject the null hypothesis and conclude that there is enough evidence to support the alternative hypothesis. On the other hand, if the p-value is greater than 0.05, we fail to reject the null hypothesis due to insufficient evidence.<\/p>\n

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