Use to Estimate via a confidence interval and perform a hypothesis test for the difference between two population proportions. If comparing more than two proportions, refer to the Chi Square Tests for a Two-Way Table guide.
Two Proportions Test
- From an open JMP® data table, select Analyze > Fit Y by X.
- Choose the binary response variable for the Y, Response.
- Choose the 2 levels variable that defines the groups for the X, Factor. Click OK.
- Select Two Sample Test for Proportions under the
top Red Triangle.
Two Sample Test for Proportions
JMP displays a Mosic Plot, Contigency Table (not shown) as well as a ChiSquare and Fisher’s Exact Tests (not shown). These tests can be used when comparing two groups and also when there are more than two groups to compare. Choosing the Two Sample Test for Proportions adds a Confidence Interval and Adjusted Wald’s Test for comparing two proportions.
Here we would estimate the difference between the two population proportions (pmarried|female - p married|male) to be 0.076 with a 95% Confidence Interval of (-0.032 , 0.182).
Here we are testing the two-sided hypothesis:
H0: pmarried|female = p married|male
HA: pmarried|female ≠ p married|male
Interpretation (using a significance level of 0.05): The p-value for this test is 0.1686 indicating there is not statistically significant evidence to conclude a difference in proportion of females vs. males in the population that are married. Note the p-value for the Wald’s Test is very similar to the Likelihood Ratio and Pearson’s ChiSquare tests.
Notes: Relative Risk and Odds Ratio, two analyses useful when comparing two proportions, are available under the Red Triangle.
The Z-Test approach for comparing two proportions can be peformed using the Hypothesis Test for Two Proportions and Confidence Intervals for Two Proportions Calculators under Help > Sample Index > Calculators or Student > Calculators in JMP Student Subscription.
Visit Basic Analysis > Contingency Analysis in JMP Help to learn more.