population parameter वाक्य
उदाहरण वाक्य
मोबाइल
- This is why the " Zafer Burunu " ( the end-nose of the peninsula ) is now a protected, natural heritage area, where marine species are slowly recovering to healthy population parameters.
- No sample ( except a complete, no-replacement census ) can tell you the " chance " that an otherwise-unknown population parameter " is " such-and-such . talk ) 08 : 09, 26 April 2014 ( UTC)
- Errors in inference, including confidence intervals that fail to include their corresponding population parameters or hypothesis tests that incorrectly reject the null hypothesis, are more likely to occur when one considers the set as a whole.
- The population mean is also a single measure; however, it is not called a statistic, because it is not obtained from a sample; instead it is called a population parameter, because it is obtained from the whole population.
- The bootstrap distribution of a point estimator of a population parameter has been used to produce a bootstrapped confidence interval for the parameter's true value, if the parameter can be written as a function of the population's distribution.
- The 95 % limits of agreement can be unreliable estimates of the population parameters especially for small sample sizes so, when comparing methods or assessing repeatability, it is important to calculate confidence intervals for 95 % limits of agreement.
- The next step is standardizing ( dividing by the population standard deviation ), if the population parameters are known, or studentizing ( dividing by an estimate of the standard deviation ), if the parameters are unknown and only estimated.
- Rather than using sample statistics as estimators of population parameters and applying confidence intervals to these estimates, one considers " the next sample " X _ { n + 1 } as " itself " a statistic, and computes its sampling distribution.
- Since prediction intervals are only concerned with past and future observations, rather than unobservable population parameters, they are advocated as a better method than confidence intervals by some statisticians, such as Seymour Geisser, following the focus on observables by Bruno de Finetti.
- In parameter confidence intervals, one estimates population parameters; if one wishes to interpret this as prediction of the next sample, one models " the next sample " as a draw from this estimated population, using the ( estimated ) " population " distribution.
- Note that a single confidence interval with 95 % coverage probability level will likely contain the population parameter it is meant to contain, i . e . in the long run 95 % of confidence intervals built in that way will contain the true population parameter.
- Note that a single confidence interval with 95 % coverage probability level will likely contain the population parameter it is meant to contain, i . e . in the long run 95 % of confidence intervals built in that way will contain the true population parameter.
- The tolerance interval differs from a confidence interval in that the confidence interval bounds a single-valued population parameter ( the mean or the variance, for example ) with some confidence, while the tolerance interval bounds the range of data values that includes a specific proportion of the population.
- Thus for inference purposes " t " is a useful " pivotal quantity " in the case when the mean and variance ( ?, ? 2 ) are unknown population parameters, in the sense that the " t "-value has then a probability distribution that depends on neither ? nor ? 2.
- However, it is a minimum variance unbiased estimate of the expected value of the median of three values and in this application of the theory it is the population parameter defined as " the expected value of the median of three values " which is being estimated, not the median of the population.
- It is not simply a matter of the population parameters ( mean and standard deviation ) being unknown it is that " regressions " yield " different residual distributions " at " different data points, " unlike " point estimators " of univariate distributions, which share a " common distribution " for residuals.
- Whereas a confidence interval's size is entirely due to sampling error, and will approach a zero-width interval at the true population parameter as sample size increases, a tolerance interval's size is due partly to sampling error and partly to actual variance in the population, and will approach the population's probability interval as sample size increases.
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