{"id":258127,"date":"2024-06-30T12:00:44","date_gmt":"2024-06-30T12:00:44","guid":{"rendered":"https:\/\/namso-gen.co\/blog\/?p=258127"},"modified":"2024-06-30T12:00:44","modified_gmt":"2024-06-30T12:00:44","slug":"what-is-your-one-sided-p-value","status":"publish","type":"post","link":"https:\/\/namso-gen.co\/blog\/what-is-your-one-sided-p-value\/","title":{"rendered":"What is your one-sided P value?"},"content":{"rendered":"

When conducting statistical analyses, it is common to calculate a p-value, which measures the strength of evidence against a null hypothesis. A p-value is a number that helps researchers determine whether their results are statistically significant. It indicates the likelihood of obtaining the observed results by chance alone.<\/p>\n

A one-sided p-value specifically looks at the probability of observing a test statistic as extreme or more extreme than the observed value, under the assumption of the alternative hypothesis being true. In simple terms, it measures the evidence in favor of a specific direction of an effect.<\/p>\n

For example, let’s say researchers are investigating the relationship between physical exercise and weight loss. They might hypothesize that exercise leads to weight loss and perform a study to test this hypothesis. In this case, a one-sided p-value helps determine if the observed results provide evidence that exercise has a significant effect on weight loss, specifically in the direction of weight reduction.<\/p>\n

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