Proportion Test

The Proportion Test computes a test statistic to determine if a specific category in a sample has a different proportion than the expected proportion, p0. The node calculates the sample proportion of the category p̂. With the given null-hypothesized proportion p0, a z-Score is calculated via (p̂ - p0)/se, where se is the standard error. If the corresponding p-Value is below the given significance level α, the null hypothesis can be rejected. Missing values will be ignored. See Wikipedia on test statistic, "One-proportion z-test" for further information.


Category column
The distribution column, of StringType or BooleanType. Its total number of occurrences without missing values is nobs.
The category to test for. The number of occurrences of this category in the category column is count.
Null hypothesis
The null hypothesized proportion 0 < p0 < 1.
Alternative hypothesis
The alternative hypothesis HA: whether the actual proportion =nobs/count is
  • larger than (GREATER_THAN)
  • less than (LESS_THAN)
  • different than (TWO_SIDED)
the null hypothesized proportion p0.
Significance level α
H0 is rejected, if p-Value < α

Advanced Settings

Use sample proportion
Whether to calculate the standard error from the sample proportion p̂ rather than the default null hypothesis proportion p0.

Input Ports

The table from which to test samples

Output Ports

Proportion test evaluation


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