Normal Distribution
nothing is called 95% until it has been counted
Concept

Welch test — where it appears

A two-sample test of means that does not assume the two groups share a variance. Its degrees of freedom are computed from the two estimated variances, and its size holds well for normal groups and drifts when the difference of the means is skewed.

Named by 2 essays across one field — each of them below, with the objects they name alongside it.

The pooled two-sample test's size, with a true null everywhere. Forty units split between two groups, with the second group's variance a stated multiple of the first's, and the two population means equal. A 5% test should reject 5% of the time. The pooled test runs from 0.55% to 18.91% across this region; Welch's runs from 4.63% to 5.51%.

A degrees of freedom that is not a count

The pooled two-sample test's size runs from 0.55% to 18.91% across forty units split five ways against five variance ratios, with a true null in every cell. Welch's runs from 4.63% to 5.51% — bought with a degrees of freedom that is a function of the data, not an integer, and not a count of anything.

tails · Student Welch's test on skewed groups: the low and high rejection rates in every cell, with equal means throughout. Each cell should read 2.5 / 2.5. Two identical exponentials at 20 and 20 read 2.04 / 2.22; the worst cell, a wide exponential against a normal at 8 and 32, reads 9.79 / 0.47.

The skewness of a difference

Welch's test holds its size to within half a point when both groups are normal. Give both groups the same skewed population and it still balances at twenty and twenty — and at eight and thirty-two it rejects low on 7.16% of samples and high on 0.66%. One number decides which: the skewness of the difference of the two means, which ranks twenty-five cells by their imbalance with a correlation of 0.997.

tails · Student

Named alongside it

The objects these essays reach for when they reach for this one.

Behrens–FisherError rateTwo-sample testAllocationCentral limit theoremDegrees of freedomEstimated varianceNeyman allocationSample sizeSkewnessStudent's t

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