Two-proportion comparison calculator

Calculate difference in sample proportions and pooled z statistic with your own figures.

Your numbers

Use the units shown. Results update as you change valid inputs.

Use difference in sample proportions and pooled z statistic to compare changes to your inputs. The method and limits below explain the scope.

Examples

Examples

Try the starting example

Group A successes
60
Group A trials
100
Group B successes
45
Group B trials
100
Difference in sample proportions
0.15
Pooled z statistic
2.123977
Two-sided p value
0.033672

Try another scenario

Group A successes
61
Group A trials
100
Group B successes
45
Group B trials
100
Difference in sample proportions
0.16
Pooled z statistic
2.266826
Two-sided p value
0.023401
Calculation method

Calculation method

Difference in sample proportions

Pooled null SE=sqrt(pooled(1-pooled)(1/nA+1/nB)); no continuity correction.

Pooled z statistic

Pooled null SE=sqrt(pooled(1-pooled)(1/nA+1/nB)); no continuity correction.

Two-sided p value

Pooled null SE=sqrt(pooled(1-pooled)(1/nA+1/nB)); no continuity correction.

Symbols and units
a
Group A successes
b
Group A trials
c
Group B successes
d
Group B trials

Use the units shown. A list keeps the order in which you enter its values. The symbol ^ means “raised to the power of”.

Assumptions & limits

Assumptions & limits

  • Independent Bernoulli trials, large-sample approximation. Supported limits: All required fields must be finite values of the exact declared type and within displayed bounds. Lists contain1–1000 finite numbers. JSON tables are numeric rectangular rows, at most100 rows and30 columns; individual tools have stricter shape/domain constraints. Independent Bernoulli trials, large-sample approximation.
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Further reading

Method reference ↗

Background reading; this does not imply endorsement or independent review of SumFizz.

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