Confidence limits
Confidence limits
Confidence limits (pronunciation: /ˈkɒnfɪdəns ˈlɪmɪts/) are a range of values, derived from a statistical estimation, that is likely to contain the value of an unknown parameter. They are used in statistical analysis and hypothesis testing to provide an estimate of the uncertainty associated with a sample statistic.
Etymology
The term "confidence limits" originates from the field of statistics. The word "confidence" comes from the Latin confidentia, meaning "trust or reliance", and "limit" comes from the Latin limes, meaning "boundary or end". Together, they represent the boundaries within which we have a certain level of confidence that the true parameter lies.
Definition
Confidence limits are defined by two values: the lower confidence limit (LCL) and the upper confidence limit (UCL). These limits form a confidence interval, which is used to quantify the amount of uncertainty in a sample estimate. The width of the confidence interval gives us an idea of how uncertain we are about the unknown parameter. A wider interval may indicate that more data should be collected before making a definitive conclusion.
Calculation
The calculation of confidence limits depends on the standard deviation of the sample, the sample size, and the desired level of confidence. The most common level of confidence is 95%, but other levels such as 90% or 99% can also be used depending on the context. The formula for calculating the confidence interval is:
CI = X ± Z * (s/√n)
where:
- CI is the confidence interval
- X is the sample mean
- Z is the Z-score, which corresponds to the desired level of confidence
- s is the sample standard deviation
- n is the sample size
Related Terms
External links
- Medical encyclopedia article on Confidence limits
- Wikipedia's article - Confidence limits
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