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Significance markers identify differences that would be unlikely under the test’s no-difference assumption. They describe statistical evidence in the current table; they do not measure business importance or establish causation.

Before you start

Open the table’s legend and identify its raw column bases, confidence levels, and tests.

Distinguish colors from letters

  • Significant cells colors compare each column percentage with the overall percentage on the same row. Green is higher and red is lower at the displayed level.
  • Column proportions test letters compare columns directly. B in column A means A is significantly higher than B.
Uppercase letters and stronger colors use the primary confidence level. Lowercase letters and lighter colors use the optional secondary level. When Also mark at 99% is on, a letter followed by an asterisk (A*) and the deepest color mark a difference that also holds at 99%. A table set to 95% primary and 90% secondary with this option therefore reads: a = 90%, A = 95%, A* = 99%. Open the crosstab Legend to confirm the active settings.

Interpret a 95% result

At a 95% confidence level, the result indicates that a difference at least this large would occur in fewer than 5% of repeated samples under the no-difference assumption used by the test. It does not mean:
  • The result is proven with 95% certainty.
  • The difference is large enough to matter to the decision.
  • One variable caused the other.
  • An unmarked difference is evidence that the groups are identical.
Report the observed size and the statistical result separately. For example: “Purchase intent was 14 points higher in column A than column B; the column-proportion test marked the difference at 95%.”

Check the unweighted base

Crosstab tests use real respondent counts even when weighted values are displayed. If all columns are below 30, no significance comparison is performed. A table without markers can therefore mean either that tests found no marked differences or that the bases were not eligible. Read the note beneath the table.

Account for repeated comparisons

A large crosstab can run many cell comparisons. At a 95% threshold, isolated markers can occur by chance across a large set of tests. Give more weight to comparisons specified in the analysis plan and to coherent patterns across related rows than to one unexpected marker found after scanning the table. Selected tables are generated by default. Only when Only keep tables with a significant difference is enabled does the plan remove comparisons without a qualifying significant cell on a raw column base of at least 30. Review that option, question eligibility and selected comparisons before diagnosing a missing table. An untested or unmarked difference is not evidence that groups are identical.

Write the result

Include:
  • The compared groups and measured answer.
  • The percentage or mean in each group.
  • The point difference where useful.
  • The unweighted bases.
  • The confidence level and test used.
  • A directional qualifier when the result is not marked or not tested.
Avoid replacing a missing test result with a claim of no difference. State that the observed difference was not significant at the selected level, or that the base was below the testing threshold.

Check the result

The written conclusion names the compared groups, values, raw bases, test, and confidence level. Distinguish an untested small base from a tested difference that was not significant.

Check repeated concept observations

A table can contain several concept answers from the same respondent. Its answer base and respondent base differ. The minimum-base rule reads respondents, not answer records; column tests, shading tests, chi-square, Fisher and confidence intervals are not computed for the repeated-record table. Do not interpret missing markers as evidence of equal concepts. Statistics beneath a chart can also show mean-comparison letters. Read those against the chart’s measure and bases, not as tests of its answer percentages.