sampling distribution sentence in Hindi
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- Generally, instrumental variables estimators only have desirable asymptotic, not finite sample, properties, and inference is based on asymptotic approximations to the sampling distribution of the estimator.
- In invariant-theoretic conditional inference, the sampling distribution is conditioned on an invariant of the group of transformations ( with respect to which the Haar measure is defined ).
- Confidence intervals and hypothesis tests are two statistical procedures in which the quantiles of the sampling distribution of a particular statistic ( e . g . the standard score ) are required.
- If the estimator is derived from a sample statistic and is used to estimate some population statistic, then the expectation is with respect to the sampling distribution of the sample statistic.
- Using one of these sampling distributions, it is possible to compute either a one-tailed or two-tailed p-value for the null hypothesis that the coin is fair.
- Because Sobel s test evaluates a given sample on the normal distribution, small sample sizes and skewness of the sampling distribution can be problematic ( see Normal Distribution for more details ).
- The most simple-minded brute force approach would be to simply make a huge sample distribution of how the system has actually hopped between any two feature values over any time interval.
- When calculated from the same population, it has a different sampling distribution to that of the mean and is generally not normal ( but it may be close for large sample sizes ).
- Further inputs to the algorithm are the marginal sample distribution p ( x ) \, which has already been determined by the dominant eigenvector of P \, and the matrix valued Kullback Leibler distance function
- The bias depends both on the sampling distribution of the estimator and on the transform, and can be quite involved to calculate see unbiased estimation of standard deviation for a discussion in this case.
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