statsmodels.stats.power.NormalIndPower.plot_power¶

NormalIndPower.
plot_power
(dep_var='nobs', nobs=None, effect_size=None, alpha=0.05, ax=None, title=None, plt_kwds=None, **kwds)¶ plot power with number of observations or effect size on xaxis
Parameters:  dep_var (string in ['nobs', 'effect_size', 'alpha']) – This specifies which variable is used for the horizontal axis.
If dep_var=’nobs’ (default), then one curve is created for each
value of
effect_size
. If dep_var=’effect_size’ or alpha, then one curve is created for each value ofnobs
.  nobs (scalar or array_like) – specifies the values of the number of observations in the plot
 effect_size (scalar or array_like) – specifies the values of the effect_size in the plot
 alpha (float or array_like) – The significance level (type I error) used in the power
calculation. Can only be more than a scalar, if
dep_var='alpha'
 ax (None or axis instance) – If ax is None, than a matplotlib figure is created. If ax is a matplotlib axis instance, then it is reused, and the plot elements are created with it.
 title (string) – title for the axis. Use an empty string,
''
, to avoid a title.  plt_kwds (None or dict) – not used yet
 kwds (optional keywords for power function) – These remaining keyword arguments are used as arguments to the
power function. Many power function support
alternative
as a keyword argument, twosample test supportratio
.
Returns: fig
Return type: matplotlib figure instance
Notes
This works only for classes where the
power
method haseffect_size
,nobs
andalpha
as the first three arguments. If the second argument isnobs1
, then the number of observations in the plot are those for the first sample. TODO: fix this for FTestPower and GofChisquarePowerTODO: maybe add line variable, if we want more than nobs and effectsize
 dep_var (string in ['nobs', 'effect_size', 'alpha']) – This specifies which variable is used for the horizontal axis.
If dep_var=’nobs’ (default), then one curve is created for each
value of