confidence intervals การใช้

• This counter-example is used to argue against na飗e interpretations of confidence intervals.
• As for what you said about confidence intervals, that is very interesting.
• Give BCa Bootstrap confidence interval to indicate the accuracy of this estimation.
• One disadvantage is that confidence intervals and evolutionary models are not constructed.
• Confidence intervals are computed to demonstrate the precision of relative risk estimates.
• The narrower the confidence interval, the more precise the relative risk estimate.
• Fieller's theorem can be used to compute confidence intervals of these ratios.
• The following formulae are used in the derivation of these confidence intervals
• This approximation gives the following values for a 95 % confidence interval:
• In most cases, reliability parameters are specified with appropriate statistical confidence intervals.
• A statistical significance test shares much mathematics with a confidence interval.
• There are several ways to compute a confidence interval for a binomial proportion.
• The actual meaning of confidence levels and confidence intervals is rather more subtle.
• Confidence intervals are usually constructed to help assess the quality of the output.
• This is necessary for the desired confidence interval property to hold.
• Because of this problem several methods to estimate confidence intervals have been proposed.
• Confidence levels and confidence intervals were introduced by Neyman in 1937.
• With the binomial distribution one can obtain a confidence interval of the prediction.
• Such procedures include Impulse Response Analysis with bootstrapped confidence intervals for VEC modelling.
• This should give a confidence interval of 2.2 at 95 %.