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The confidence level is a statistical concept that indicates the confidence or certainty with which one can draw a conclusion from the results of a sample to the totality (population). It is often used in inferential statistical analysis to make statements about parameters such as the mean, standard deviation, or proportion in a population.
The confidence level is usually expressed as a percentage and indicates the proportion of possible samples that would yield the same conclusion. For example, a confidence level of 95% means that 95% of the samples from the same population would yield similar results.
The determination of the confidence level depends on the type of analysis and the requirements of the study. A confidence level of 95% is often used, as this is a common practice and represents a reasonable compromise between certainty and precision. A confidence level of 99% is sometimes used when a higher degree of certainty is required, but this may result in wider confidence intervals.
It is important to note that the confidence level says nothing about the accuracy or probability of the result itself. It refers only to the percentage of samples that would yield similar results if the sample were drawn again.