the likelihood that the sampling error in a survey result will fall within a specified range, usually expressed in terms of standard errors (e.g. 1 standard error equals 68% likelihood; 2 standard errors equals 95% likelihood).
The level of certainty to which an estimate can be trusted. The degree of certainty is expressed as the chance that a true value will be included within a specified range, called a confidence interval.
the percentage of times that a sample would be expected to fall by chance outside the confidence interval; risk level. At the .05 confidence level, only 5 percent of the time would a person's score fall by chance outside the confidence interval. Cp. statistical significance.
A measurement of the likelihood that an inductive generalization will produce a true conclusion. Confidence level indicated the percentage of random samples in which the property in question occurs within the error margin. (Note: do not take confidence level in psychological terms, as a measure of how sure a person happens to feel about some generalization. It is a quantifiable measurement of a generalization's actual application to random samples.)
The probability that a confidence interval or region will contain the true parameters is given by the confidence level. A 95% confidence interval will contain the true parameters 95% of the time on average. Usually a confidence level of 95% or greater is considered statistically significant.
The specific probability of obtaining some result from a sample if it did not exist in the population as a whole, at or below which the relationship will be regarded as statistically significant (Alreck, 444).
The probability of accepting the null hypothesis when it is true - for example the probability that test results will detect disease when the true prevalence is greater than or equal to the specified design prevalence.
Dynamic Logic uses a 90% confidence level. It is the probability that if a metric increases at 90%, the odds are 90 to 10 that the same metric increased among everyone who saw the ad. If a lower confidence level is used, the odds are too high that the difference between the Control and Exposed groups can be attributed to sampling error and not the ad campaign.
A Confidence Level is used during Monte Carlo Simulations to indicate that a certain percentage of the simulated equity curves demonstrated results for a particular measure that were greater than the confidence level. For example, a 95% Confidence Level MAR Ratio of 0.8 indicates that 95% of the simulation iterations showed a MAR Ratio of 0.8 or better.
The fraction of measurements that can be expected to lie within a given range. Thus if m = (15.34 ± 0.18) g, at 67% confidence level, 67% of the measurements lie within (15.34 - 0.18) g and (15.34 + 0.18) g. If we use 2 deviations (±0.36 here) we have a 95% confidence level.
The likelihood that the true value of a variable is within a confidence interval. For example, for confidence intervals at the 95% level, we are statistically 95% certain that the actual value of the variable is within the interval.