code: def get_p_vals(self, X):
  		'''
  		Parameters
  		----------
  		X : np.array
  			Array of word counts, shape (N, 2) where N is the vocab size.  X[:,0] is the
  			positive class, while X[:,1] is the negative class. None by default
  
  		Returns
  		-------
  		np.array of p-values
  
  		'''
  		z_scores = self.get_scores(X[:, 0], X[:, 1])
  		return norm.cdf(z_scoresf get_p_vals(self, X):
  		'''
  		Parameters
  		----------
  		X : np.array
  			Array of word counts, shape (N, 2) where N is the vocab size.  X[:,0] is the
  			positive class, while X[:,1] is the negative class. None by default
  
  		Returns
  		-------
  		np.array of p-values
  
  		'''
  		z_scores = self.get_scores(X[:, 0], X[:, 1])
  		return norm.cdf(z_scores)
docs: Parameters
  		----------
  		X : np.array
  			Array of word counts, shape (N, 2) where N is the vocab size.  X[:,0] is the
  			positive class, while X[:,1] is the negative class. None by default
  
  		Returns
  		-------
  		np.array of p-values