# Tukey HSD plot_simultaneous - how does it work?

I have performed a Tukey HSD in Python. I am not sure what values are plotted when using the .plot_simultaneous() command (see statsmodels documentation).

The resulting plot is: I am wondering: how is the resulting mean and std calculated?

How can I interpret the graphic result of this?

## 1 Answer

Take this plot for example: I have a data set of US climate normals for various stations and I've grouped those station by Physiographic province. The plot shows the means (black dot) and the 95% confidence interval (not standard deviation) for each group.

You can interpret my plot as follows. For the Wyoming Basin, it is significantly drier than say the Valley and ridge province, but it is not drier than the southern rocky mountains, bc they have overlapping confidence intervals.

• So does this mean these are just the usual mean and 95% confidence intervals, not some combined value? I could not understand this from the documentation. Thank you! – Moiraine24 Oct 11 '18 at 11:42
• The mean is just the mean for each group. The CI is the 95% CI determined using the Tukey's Q critical value to compute the width of each groups CI. statsmodels.org/dev/generated/… – June Skeeter Oct 14 '18 at 22:13
• The Q value is determined based off the confidence level, the degrees of freedom, and the number of groups. So basically, the CI is based calculated using the Tukeys's Q value, rather than a say a t value like if you were doing a student's t test. See this table for an example. real-statistics.com/statistics-tables/studentized-range-q-table – June Skeeter Oct 14 '18 at 22:24