class_docstr: Dummy regressor that uses a univariate statistic to make predictions.
  
  Parameters
  ----------
  statistic
  
  Examples
  --------
  
  >>> from pprint import pprint
  >>> from river import dummy
  >>> from river import stats
  
  >>> sentences = [
  ...     ('glad happy glad', 3),
  ...     ('glad glad joyful', 3),
  ...     ('glad pleasant', 2),
  ...     ('miserable sad glad', -3)
  ... ]
  
  >>> model = dummy.StatisticRegressor(stats.Mean())
  
  >>> for sentence, score in sentences:
  ...     model.learn_one(sentence, score)
  
  >>> new_sentence = 'glad sad miserable pleasant glad'
  >>> model.predict_one(new_sentence)
  1.25
code: def _unit_test_params(cls):
      yield {"statistic": stats.Mean()}
  
imports: from __future__ import annotations
  import collections
  from river import base, stats
label_desc: Use image node_id 2 for calling the StatisticRegressor obj's underlying member method code with example usage: obj._unit_test_params(cls) without return types