new_contents: #!/usr/bin/env python2
  # -*- coding: utf-8 -*-
  """
  Created on Tue Jun 26 12:08:31 2018
  
  @author: sjjoo
  """
  #%%
  import numpy as np
  from sklearn import linear_model as lm
  import statsmodels.api as sm
  
  import statsmodels.formula.api as smf
  import pandas as pd
  
  X = np.column_stack((temp_read,temp_raw, temp_age,temp_meg1, temp_meg2))
  y = temp_meg2
  
  reg = lm.LinearRegression()
  reg.fit(X,y)
  
  
  d = pd.DataFrame(X,columns=['read', 'raw', 'age','meg_dot', 'meg_lex'])
  result1 = smf.ols('meg_dot~read',d).fit()
  result2 = smf.ols('meg_dot~age',d).fit()
  
  result3 = smf.ols('meg_dot~read+age',d).fit()
  print(result1.summary())
  print(result2.summary())
  print(result3.summary())
  
  result4 = smf.ols('meg_dot~meg_lex',d).fit()
  
  print(result4.summary())
  
  result5 = smf.ols('meg_dot~raw+age',d).fit()
  
  print(result5.summary())
subject: add linear_regression