name: op-overlay-z-vs-ref
kind: operator
category: OVERLAY
operator: OVERLAY_Z_VS_REF
description: Compose-host per-group two-sample z-test on the means against the reference slot's matching group (SERIES); parity overlay reading from CellComponents.
type: reference
applies_to: compose
examples_tags: [overlay, compose, hypothesis-test, z, byte-equal-test]
Compose-only parity overlay. Series-shape sibling of the cell z overlay. Overlays decorate the host; no Response.Components.
Use when
Large-sample z-test for every group of a grouped result in a Compose request: does the target’s mean differ from the reference’s?
Questions it answers:
- With large samples, which regions’ average spend changed since last quarter?
- Which high-volume channels’ average basket differs between the two periods?
Use something else:
OVERLAY_T_VS_REFwhen any group is small; the t-based version is more honest there.
Params
Scope required, must be group. Reference / Targets required slot labels. Optional params.variance_target/_ref (float, 1.0), params.sample_size_target/_ref (int, 2). Without AGG_WELFORD these apply to EVERY group: p-values then describe the supplied values, not each group.
multiplicity— optional{method, family, alpha}; addsp_adjustedfigures, raw p untouched (multiplicity-correction).
Host shape
COMPOSE — SERIES grouped Process on both slots. Parity overlay — reads {n, mean, variance} from Response.Components.Crosstab.CellComponents (matrix arms via AGG_WELFORD), else the params triple. Renders as a per-group strip.
Output
SERIES — one SeriesEntry per host group key carrying the p-value on Summary.Statistic. One layer per target; Baseline unset.
Reading the output
summary.statistic: a p-value. Below alpha (0.05 unless the request sets another) the result is called significant; that is not the same as important, so read the effect size for how big it is.- Caveat: Despite the field name, each series entry’s summary.statistic holds that group’s two-sided z-test p-value, not a z value; Pulse does not emit z.
- Caveat: It is read from the normal curve, so with small groups it comes out too small.
Gotchas
- Weighted (both kinds): a row triple carrying
sum_weightsreads N* =sum_weights(frequency) orn_eff(probability), never the rawn, and its variance fromm2on w*.Summary.Parametersaddssum_weights(+n_eff) over the legs read. - Byte-equal to the two-sample z-test on the same inputs — shares
normalTwoSidedPwith it and the cell z overlay. - Missing reference row, or degenerate inputs (
se == 0,n < 2) →PULSE_OVERLAY_REF_ZEROwithref_missing=true, entry NaN. - Unlike the streamable SERIES arm of the reference index / delta: inferential, buffered.