class_docstr: Statistical Power calculations for one sample chisquare test
  
      
class_docstr_tok: ["Statistical","Power","calculations","for","one","sample","chisquare","test"]
docstr: Calculate the power of a chisquare test for one sample
  
  Only two-sided alternative is implemented
  
  Parameters
  ----------
  effect_size : float
      standardized effect size, according to Cohen's definition.
      see :func:`statsmodels.stats.gof.chisquare_effectsize`
  nobs : int or float
      sample size, number of observations.
  alpha : float in interval (0,1)
      significance level, e.g. 0.05, is the probability of a type I
      error, that is wrong rejections if the Null Hypothesis is true.
  n_bins : int
      number of bins or cells in the distribution.
  
  Returns
  -------
  power : float
      Power of the test, e.g. 0.8, is one minus the probability of a
      type II error. Power is the probability that the test correctly
      rejects the Null Hypothesis if the Alternative Hypothesis is true.
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code: def power(
      self, effect_size, nobs, alpha, n_bins, ddof=0
  ):  # alternative='two-sided'):
      """Calculate the power of a chisquare test for one sample
  
      Only two-sided alternative is implemented
  
      Parameters
      ----------
      effect_size : float
          standardized effect size, according to Cohen's definition.
          see :func:`statsmodels.stats.gof.chisquare_effectsize`
      nobs : int or float
          sample size, number of observations.
      alpha : float in interval (0,1)
          significance level, e.g. 0.05, is the probability of a type I
          error, that is wrong rejections if the Null Hypothesis is true.
      n_bins : int
          number of bins or cells in the distribution.
  
      Returns
      -------
      power : float
          Power of the test, e.g. 0.8, is one minus the probability of a
          type II error. Power is the probability that the test correctly
          rejects the Null Hypothesis if the Alternative Hypothesis is true.
  
      """
      from statsmodels.stats.gof import chisquare_power
  
      return chisquare_power(effect_size, nobs, n_bins, alpha, ddof=0)
  
imports: import warnings
  import numpy
  from scipy import stats, optimize, special
  from statsmodels.tools.rootfinding import brentq_expanding
label_desc: Use image node_id 1 for calling the GofChisquarePower obj's underlying member method code with example usage: obj.power(effect_size, nobs, alpha, n_bins, ddof) and returns: chisquare_power