{"id":171065,"date":"2023-11-16T05:12:46","date_gmt":"2023-11-16T05:12:46","guid":{"rendered":"https:\/\/namso-gen.co\/blog\/how-to-find-confidence-interval-from-p-value\/"},"modified":"2023-11-16T05:12:46","modified_gmt":"2023-11-16T05:12:46","slug":"how-to-find-confidence-interval-from-p-value","status":"publish","type":"post","link":"https:\/\/namso-gen.co\/blog\/how-to-find-confidence-interval-from-p-value\/","title":{"rendered":"How to find confidence interval from p-value?"},"content":{"rendered":"

When working with statistical data, researchers often need to determine the relationship between a sample statistic and a population parameter. One common way to do this is by calculating a confidence interval based on the p-value. Here’s how to find confidence interval from p-value:<\/p>\n

**Calculate the z-score associated with the p-value.**<\/p>\n

To find the confidence interval from a p-value, you first need to calculate the z-score associated with the p-value. This z-score represents the number of standard deviations away from the mean that the p-value falls. <\/p>\n

Next, use the z-score to determine the confidence level. For example, a z-score of 1.96 corresponds to a 95% confidence level. <\/p>\n

Finally, calculate the confidence interval using the formula: <\/p>\n

Confidence Interval = Sample Statistic +\/- (Z-Score * Standard Error)<\/p>\n

By following these steps, you can find the confidence interval from a given p-value and determine the range in which the population parameter is likely to fall.<\/p>\n

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