confidence level
In statistics, the confidence level refers to the degree of certainty or reliability associated with an estimate or inference
In statistics, the confidence level refers to the degree of certainty or reliability associated with an estimate or inference. It measures the probability or level of confidence that a calculated interval, parameter estimate, or hypothesis test result contains the true value of the population parameter being investigated.
The confidence level is typically expressed as a percentage and is directly related to the margin of error or variability of the estimate. Commonly used confidence levels include 90%, 95%, and 99%, although other levels can also be used depending on the situation.
For example, if a 95% confidence level is used for estimating a population mean, it means that if the sampling procedure were repeated numerous times, approximately 95% of the calculated confidence intervals would contain the true population mean.
A higher confidence level provides more confidence in the estimate or inference being made, but it also widens the confidence interval, resulting in a larger margin of error. Conversely, a lower confidence level would yield a narrower interval with a smaller margin of error, but with less certainty in the estimate.
The choice of confidence level depends on the importance of being correct, the amount of available data, the level of variability in the data, and the consequences of accepting or rejecting the estimate or inference.
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