dataFrame.columns.stat — confidenceIntervalWilson()

Description

The confidenceIntervalWilson() method of the stat object computes the Wilson confidence interval for the proportion represented by the selected binary columns.

Signature

dataFrame.columns(...columnNames).stat.confidenceIntervalWilson()
Scope
columns
Family
stat
Returns
object

Argument

...columnNames ( string[] )
The name of the columns from which to compute the Wilson confidence interval

Returns

stat (object)
A statistic object containing the Wilson confidence interval and related statistics.
estimate (number)
The estimated proportion.
ci (object)
The confidence interval bounds.
lower (number)
The lower confidence interval bound.
upper (number)
The upper confidence interval bound.
margin (object)
The distance between the estimate and the confidence interval bounds.
lower (number)
The distance between the estimate and the lower bound.
mean (number)
The mean of the lower and upper margins.
upper (number)
The distance between the estimate and the upper bound.

Notes

  • The method is intended for binary data.
  • The method applies the Wilson score interval for estimating a binomial proportion.
  • Wilson intervals generally provide better coverage than the normal approximation, especially for small samples or proportions near 0 or 1.
  • The confidence interval may be asymmetric around the estimate.
  • margin.mean is calculated as the average of margin.lower and margin.upper.
  • Negative values indicate that the second selected column has a larger mean than the first selected column.

Example

// calculate the confidence interval for 2 columns of the dataFrame
var stat = dataFrame.columns('groupA', 'groupB').stat.confidenceIntervalWilson();

// log the stat details
notebook.log(stat);