Question

Biostatistics

How to interpret confidence intervals and confidence levels?

Why the p-value is important?

Answer 1

Answer: Confidence intervals is affected by any of the factors such as: population size that does not usually affect the Confidence intervals but can be a factor if working with small and known groups of people. Sample Size can effect the confidence intervals as the smaller the sample will be, there is less chance that can be confident and the results will show the true population parameter. Confidence Intervals is mainly consists about the risk, mostly 90% of the confidence intervals are used.

A 0% confidence level means that there is no faith at all that if the survey is repeated the result will be the same. Whereas 100% confidence level means there is no doubt at all that the survey is repeated then there will be the same results. But in statics, there is no 100% confidence level.

The p-value is important as it indicates that the null hypothesis is true and also indicates that the effect is large or that the result is of major theoretical, clinical or practical importance. A non-significant result, leading not to reject the null hypothesis, is evidence that the null hypothesis is true.