Definition Confidence level

In statistics, the confidence level indicates the probability with which the estimation of the location of a statistical parameter (e.g., an arithmetic mean) in a sample survey is also true for the population.

When conducting a survey, confidence levels must be established in advance, as the margin of error as well as the necessary scope of the survey depends on them. In surveys, confidence levels of 90/95/99% are frequently used.

If the confidence level is established at 95%, a calculated statistical value that was based on a sample is also true for the whole population within the established confidence level – with a 95% chance. In other words: the chances are very high that the arithmetic mean (as a statistical value) of a population is exactly within the margins of error which were established for the survey based on a sample.

Conversely, there is a chance that for frequently repeated surveys with new samples, in 5 cases out of 100, one calculates an arithmetic mean that does not fall within in the confidence interval of the population. The result of the survey is correct for the respondents themselves, but it is not representative of the surveyed group.

An example: A survey asked 2,000 Americans over the age of 14 whether they were in favor of the smoking ban in restaurants. Overall, 75% of the respondents answered "yes." The confidence level for the survey had been set at 95%, and the margin of error had been set at 2%.

Due to the confidence level, there is a probability of 95%, that the actual percentage of supporters is within a range of 73-77%, i.e., within the confidence interval (=result +/- margin of error). If we were to conduct the survey 100 times, each with 2,000 different participants, 95 times out of 100, the number of supporters would also be within 73-77%. However, five times out of 100, a smaller or greater number of people would answer "yes."