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This is because () is the smallest in each one of the intersection sub-families and the size of the sub-families is at most , such that the Bonferroni threshold larger than /. The same rationale applies for H ( 2 ) {\displaystyle H_{(2)}} .
The formula for the population standard deviation (of a finite population) can be applied to the sample, using the size of the sample as the size of the population (though the actual population size from which the sample is drawn may be much larger).
With respect to FWER control, the Bonferroni correction can be conservative if there are a large number of tests and/or the test statistics are positively correlated. [ 9 ] Multiple-testing corrections, including the Bonferroni procedure, increase the probability of Type II errors when null hypotheses are false, i.e., they reduce statistical ...
The bias-corrected and accelerated ... but with a different formula (note the inversion of the left and right quantiles): ... for a sample size n; this ...
The probability density function (PDF) for the Wilson score interval, plus PDF s at interval bounds. Tail areas are equal. Since the interval is derived by solving from the normal approximation to the binomial, the Wilson score interval ( , + ) has the property of being guaranteed to obtain the same result as the equivalent z-test or chi-squared test.
However, the sample size required for the sample means to converge to normality depends on the skewness of the distribution of the original data. The sample can vary from 30 to 100 or higher values depending on the skewness. [23] [24] F For non-normal data, the distribution of the sample variance may deviate substantially from a χ 2 distribution.
The case that the x variable arises randomly is known as the structural model or structural relationship.For example, in a medical study patients are recruited as a sample from a population, and their characteristics such as blood pressure may be viewed as arising from a random sample.
An alternative correction that is believed to be less conservative is the Huynh–Feldt correction (1976). As a general rule of thumb, the Greenhouse–Geisser correction is the preferred correction method when the epsilon estimate is below 0.75. Otherwise, the Huynh–Feldt correction is preferred. [3]