text: """Spector and Mazzeo (1980) - Program Effectiveness Data"""
  
  __docformat__ = 'restructuredtext'
  
  COPYRIGHT   = """Used with express permission of the original author, who
  retains all rights. """
  TITLE       = __doc__
  SOURCE      = """
  http://pages.stern.nyu.edu/~wgreene/Text/econometricanalysis.htm
  
  The raw data was downloaded from Bill Greene's Econometric Analysis web site,
  though permission was obtained from the original researcher, Dr. Lee Spector,
  Professor of Economics, Ball State University."""
  
  DESCRSHORT  = """Experimental data on the effectiveness of the personalized
  system of instruction (PSI) program"""
  
  DESCRLONG   = DESCRSHORT
  
  NOTE        = """
  Number of Observations - 32
  
  Number of Variables - 4
  
  Variable name definitions::
  
      Grade - binary variable indicating whether or not a student's grade
              improved.  1 indicates an improvement.
      TUCE  - Test score on economics test
      PSI   - participation in program
      GPA   - Student's grade point average
  """
  
  import numpy as np
  import statsmodels.tools.datautils as du
  from os.path import dirname, abspath
  
  def load():
      """
      Load the Spector dataset and returns a Dataset class instance.
  
      Returns
      -------
      Dataset instance:
          See DATASET_PROPOSAL.txt for more information.
      """
      data = _get_data()
      return du.process_recarray(data, endog_idx=3, dtype=float)
  
  def load_pandas():
      """
      Load the Spector dataset and returns a Dataset class instance.
  
      Returns
      -------
      Dataset instance:
          See DATASET_PROPOSAL.txt for more information.
      """
      data = _get_data()
      return du.process_recarray_pandas(data, endog_idx=3, dtype=float)
  
  def _get_data():
      filepath = dirname(abspath(__file__))
  ##### EDIT THE FOLLOWING TO POINT TO DatasetName.csv #####
      data = np.recfromtxt(open(filepath + '/spector.csv',"rb"), delimiter=" ",
                           names=True, dtype=float, usecols=(1,2,3,4))
      return data
  