Field

Shape, and what it does to a two-sample test

A t interval survives a skewed source in total and not in its tails. On an exponential source at 120 observations a 95% interval covers 94.81% while missing below the mean on 4.08% of samples and above it on 1.11%. The pooled two-sample test's size runs from 0.55% to 18.91% across forty units with a true null in every cell, and Welch's stays between 4.63% and 5.51% — on normal populations. On skewed ones Welch's tails are decided by one number, the skewness of the difference of the two means: two identical exponentials balance at twenty and twenty and reject low on 7.16% of samples at eight and thirty-two. And the side a decision reads needs its own repair: widened until its total coverage is exactly 95%, a t interval's upper limit on thirty exponential observations is still exceeded on 4.69% of samples, where Hall's transformation takes it to 3.31%.

Which side a 95% t interval misses on, exponential source. Both tails should be 2.5%. At 8 observations the interval falls short of the mean on 9.75% of samples and overshoots on 0.31%. At 500 they are 3.31% and 2.05%, and the total is 5.36% — which a coverage table reports as very nearly right.

Where the two tails disagree

A 95% t interval on an exponential source at 120 observations covers 94.81%, which reads as very nearly right. It misses below the mean on 4.08% of samples and above on 1.11% — one tail 63% too heavy and the other 56% too light, and the total is the statistic that hides 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.

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.

Four 95% intervals for the mean of 30 exponential observations, split by the side they miss on. Both bars should read 2.5%. The t interval misses below the mean on 6.38% of samples. Widened until its total is exactly 5%, it misses below on 4.69% and above on 0.30%. Hall's transformation misses below on 3.31% and above on 1.96%.

The side a bound is read from

On thirty exponential observations the upper limit of a 95% t interval is exceeded by the true mean 6.38% of the time, against the 2.5% a safety margin set from it assumes. Widen the interval until its total coverage is exactly 95% and the upper limit is still exceeded 4.69% of the time. A symmetric repair fixes the number that is reported and not the one that is used; Hall's transformation, which bends the interval, takes the same rate to 3.31%.

Five upper limits for the mean of 15 observations from a exponential source, by margin and by failure rate. t limit: exceeded 8.51% at a mean margin of 0.523; Hall's transformation: exceeded 4.61% at a mean margin of 1.038; gamma family, shape known: exceeded 2.59% at a mean margin of 0.787; gamma family, shape by likelihood: exceeded 4.04% at a mean margin of 0.746; gamma family, shape by skewness: exceeded 17.51% at a mean margin of 0.421. The maximum-likelihood shape has a median of 1.10 and the skewness-based shape 3.20, against a true shape of 1.

A limit from the family it came from

On fifteen exponential observations an upper limit for the mean built from the gamma family's own exact pivot, with the shape estimated by maximum likelihood, is exceeded 4.04% of the time at a mean margin of 0.746 standard deviations. Hall's transformation is exceeded 4.61% at 1.038, and the same family limit with the shape read from the sample skewness is exceeded 17.51%. Knowing the family and estimating its one parameter well recovers most of what knowing the population buys — and the parameter is estimated well only from the logarithms.

Expected loss of three upper limits against the level each is set at, fifteen exponential observations, penalty 20. A failure costs 20 standard deviations of margin. At the conventional 97.5% the t limit's loss is 2.143, Hall's 1.922 and the fitted family's 1.530. Each at its own best level: the t limit 1.263 at 99.95%, Hall's 1.862 at 98.50%, the family 1.308 at 99.25%. The best fixed multiple of the standard error costs 1.255.

The level a limit should be set at

When a failure costs twenty times a standard deviation of margin, a t limit on fifteen exponential observations set at the conventional 97.5% has an expected loss of 2.143. Set at 99.95%, the same formula's loss is 1.263 — within 1% of the best any fixed multiple of s/√n can do, and ahead of both Hall's transformation and the fitted gamma family at their own best levels. Hall's is the worst at every level on every source. Choosing the level does more than choosing the construction, and the correction that reads the sample is the one no level rescues.

Expected loss of three upper limits against the level each is set at, when a failure is charged by its size, fifteen exponential observations, penalty 20. A failure costs 20 times the distance, in standard deviations, by which the mean exceeds the limit. At the conventional 97.5% the t limit's loss is 0.728, Hall's 1.136 and the fitted family's 0.835. Each at its own best level: the t limit 0.726 at 97.00%, Hall's 0.805 at 90.00%, the family 0.735 at 92.50%.

A failure charged by its size

Charge an upper limit's failure by how far the true mean exceeds it rather than by a fixed amount, and the level a limit should be set at falls further than any other change in this comparison moves it: on fifteen exponential observations, a penalty of twenty per standard deviation of shortfall asks for a t limit at 97% where a penalty of twenty per failure asked for 99.95%. The failures are small whichever limit produces them — about an eighth of a standard deviation — so a charge by size is a small charge per failure. The ranking hardly moves: the t limit stays within about 1% of the fitted family, whose failures are no smaller than its own, and Hall's transformation stays last by 11%.

What it costs to set the t limit at one level without knowing which skewed source the 15 observations came from. For the t limit on 15 observations, charged twenty per standard deviation of shortfall plus its margin, the loss at each nominal level as an excess over the best level for each source. The best levels are 97% for the exponential, 96.25% for the gamma, shape 2, 97.75% for the gamma, shape ½, 98.25% for the lognormal. The minimax level, 97.25%, costs at most 0.8% on any of them: 0.1% on the exponential, 0.6% on the gamma, shape 2, 0.2% on the gamma, shape ½, 0.8% on the lognormal. The conventional 97.5% costs up to 1.0%.

A level set before the source is known

Every best level for an upper limit on skewed data was found knowing the source, and the fifteen observations that would tell the sources apart are the ones being used to set the limit. Chosen instead to protect the worst of four skewed sources, the t limit's level is 97.25% when a failure is charged by the size of its shortfall, and it costs at most 0.8% more than each source's own best — the sources disagree about the best level and agree that missing it a little is cheap. The fitted gamma family, the construction meant to adapt to the source, is the one that needs it: its best levels run from 90% to 96.5% and its minimax level costs 3.4%. Charged a fixed amount per failure, the t limit's minimax level is 99.97% and costs 6.5%; the conventional 97.5% costs up to 119.9%.

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