scipy.stats._result_classes.TukeyHSDResult.

# confidence_interval#

TukeyHSDResult.confidence_interval(confidence_level=0.95)[source]#

Compute the confidence interval for the specified confidence level.

Parameters:
confidence_levelfloat, optional

Confidence level for the computed confidence interval of the estimated proportion. Default is .95.

Returns:
ci`ConfidenceInterval` object

The object has attributes `low` and `high` that hold the lower and upper bounds of the confidence intervals for each comparison. The high and low values are accessible for each comparison at index `(i, j)` between groups `i` and `j`.

References

[1]

NIST/SEMATECH e-Handbook of Statistical Methods, “7.4.7.1. Tukey’s Method.” https://www.itl.nist.gov/div898/handbook/prc/section4/prc471.htm, 28 November 2020.

Examples

```>>> from scipy.stats import tukey_hsd
>>> group0 = [24.5, 23.5, 26.4, 27.1, 29.9]
>>> group1 = [28.4, 34.2, 29.5, 32.2, 30.1]
>>> group2 = [26.1, 28.3, 24.3, 26.2, 27.8]
>>> result = tukey_hsd(group0, group1, group2)
>>> ci = result.confidence_interval()
>>> ci.low
array([[-3.649159, -8.249159, -3.909159],
[ 0.950841, -3.649159,  0.690841],
[-3.389159, -7.989159, -3.649159]])
>>> ci.high
array([[ 3.649159, -0.950841,  3.389159],
[ 8.249159,  3.649159,  7.989159],
[ 3.909159, -0.690841,  3.649159]])
```