interval estimate


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interval estimate

n
(Statistics) statistics an interval within which the true value of a parameter of a population is stated to lie with a predetermined probability on the basis of sampling statistics. Compare point estimate
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How to define expected value of an interval estimate. On the set of all intervals, addition is naturally defined as
Estimation of parameter for proportion for population was presented as interval estimate (lower, upper) at 80% confidence level, calculated through an online statistical calculator.7
The 95% confidence interval estimate for mean height of breast cancer patients in urban and rural areas, are given in Table-3.
For example, if a sample estimate of 150,000 returns is known to have a coefficient of variation of 2 percent, then the following arithmetic procedure would be followed to construct a 68-percent confidence interval estimate:
A confidence interval is an interval estimate of a population parameter.
Varying these parameters widely (cutting them in half and doubling them) does not affect the magnitude of the welfare gains very much and does not affect whether any interval estimate lies entirely above zero.
Note that the Wald interval is only valid when p [member of] (0,1), as the interval estimate is reduced to either of the singular values {0,1} on the endpoints.
For a ten percentage point increase in the percent of assets held in stock outside of retirement accounts, the odds that the household exhibits the wealth effect increases by five percentage points, with a confidence interval estimate of between one and ten percent.
The comparison is based on the posterior variance, the Bayesian interval estimate, the coefficient of skewness of the posterior distribution and the Bayes posterior risk.
Key words: statistical software; tetrachoric correlation; approximation; point estimate; interval estimate.
Therefore, a model maybe much less (or much more) accurate locally, than its global confidence interval estimate. In essence, this amounts to assuming an identical distribution for prediction error that is independent of the input conditions, which is inconsistent with most real scenarios.
confidence interval, and since t is defined in equation 6.8, we substitute this for t in the confidence interval probability statement in equation 6.9 and solve for [mu] to obtain our interval estimate, and our 100(1 - [alpha]) percent confidence interval for v, appears in equation 6.10.