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CONFIDENCE INTERVAL
Confidence interval (CI) can be defined as a type of interval estimation of a population parameter which is used to indicate the reliability of an estimate. It is an observed interval that is calculated from the observations in principle it is different from sample to sample. It frequently includes the parameter of interest if the experiment is repeated.
The parameter that is contained in the observed interval is determined by the confidence level or confidence coefficient. The meaning of the term "confidence level" is that the confidence intervals include many separate data analyses of repeated and different experiments than the proportion of such intervals contain the true value of the parameter that will match the confidence level.
This is assured by the underlying construction of confidence intervals where as two-sided confidence limits form a confidence interval, their one-sided counterparts are referred to as lower or upper confidence bounds.
Confidence intervals consist of a range of values that act as good estimates of the unknown population parameter and in infrequent cases, none of these values may cover the value of the parameter.
Confidence interval Homework Help
The level of confidence would indicate the probability that the confidence range captures the true population parameter given a distribution of samples and it does not describe any single sample. This value is expressed in percentage and if it is said that 99% confident, then the true value of the parameter is in the confidence interval" and it means 99% of the observed confidence intervals will hold the true value of the parameter.
When a sample is taken, the population parameter is either in the interval made or not, there is no chance and usually, the desired level of confidence is set by the researcher. If a corresponding hypothesis test is performed, the confidence level come up with a level of significance that is 95% confidence interval reflects a significance level of 0.05, and the confidence interval includes the parameter values. If it is tested it should not be rejected with the same sample.
A confidence interval does not calculate the true value of the parameter that has a particular probability of being in the confidence interval given the data that is actually obtained. The interval intended to have such a property is called a credible interval which can be estimated using Bayesian statistics.
