class_docstr: A class for ANOVA and comparing means.
  
  Parameters
  ----------
  
  endog : list of arrays
      endog should be a list containing 1 dimensional arrays.  Each array
      is the data collected from a certain group.
class_docstr_tok: ["A","class","for","ANOVA","and","comparing","means",".","Parameters","--","--","--","--","--","endog",":","list","of","arrays","endog","should","be","a","list","containing","1","dimensional","arrays",".","Each","array","is","the","data","collected","from","a","certain","group","."]
code: def __init__(self, endog):
      self.endog = endog
      self.num_groups = len(self.endog)
      self.nobs = 0
      for i in self.endog:
          self.nobs = self.nobs + len(i)
  
file_path: statsmodels/statsmodels/emplike/elanova.py
imports: import numpy
  from .descriptive import _OptFuncts
  from scipy import optimize
  from scipy.stats import chi2
label_desc: Use image node_id 1 to create a new ANOVA object from inherited base classes: _ANOVAOpt with example: obj = ANOVA(endog)