What is the difference between Confidence Intervals and P-value?

Expert Solution

p-values, in statistical hypothesis testings, are used to determine whether a null hypothesis formulated before the performance of the study is to be rejected or not. It is the value of the probability which reflects the measure of evidence against the null hypothesis. Small p-values correspond to strong evidence against the null hypothesis. If the p-value is less than the level of significance, we reject the considered null hypothesis.

Confidence Intervals, on the other hand, is a range of values that is likely to contain an unknown population parameter of interest. It plays a vital role in interval estimation. If a 95% confidence interval says that the true population mean lies between 10 to 20 then there is 95% chance that the confidence interval contains the true value of the unknown parameter. (It is not the same saying that the unknown parameter lies in the interval 95% times since it is a parameter, not a random variable, so its value doesn't change).

orchestra answered 1 year ago

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