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The difference between any two means in a set of n means is significant provided the range of each and every subset which contains the given means is significant according to an level range test where =, = () and is the number of means in the subset concerned.
Fieller showed that if a and b are (possibly correlated) means of two samples with expectations and , and variances and and covariance , and if ,, are all known, then a (1 − α) confidence interval (m L, m U) for / is given by
In statistics, the Behrens–Fisher problem, named after Walter-Ulrich Behrens and Ronald Fisher, is the problem of interval estimation and hypothesis testing concerning the difference between the means of two normally distributed populations when the variances of the two populations are not assumed to be equal, based on two independent samples.
A binary equaliser (that is, an equaliser of just two functions) is also called a difference kernel.This may also be denoted DiffKer(f, g), Ker(f, g), or Ker(f − g).The last notation shows where this terminology comes from, and why it is most common in the context of abstract algebra: The difference kernel of f and g is simply the kernel of the difference f − g.
A paired difference test, better known as a paired comparison, is a type of location test that is used when comparing two sets of paired measurements to assess whether their population means differ. A paired difference test is designed for situations where there is dependence between pairs of measurements (in which case a test designed for ...
Dunnett's test's calculation is a procedure that is based on calculating confidence statements about the true or the expected values of the differences ¯ ¯, thus the differences between treatment groups' mean and control group's mean.
This equation has the same two solutions as the original one: = and = We can also modify the solution set by squaring both sides, because this will make any negative values in the ranges of the equation positive, causing extraneous solutions.
(The notation | x | means the absolute value of x; the magnitude of x with the sign set to +, regardless of the original sign of x.) This q s test statistic can then be compared to a q value for the chosen significance level α from a table of the studentized range distribution .