exercise1:
  Find best linear model for two items of temperature data.
  Data from two_temperatures_data.txt involves n = 2 items with dimension d = 2
  Data statistics:
    Min      =  [32.  0.]
    Max      =  [212. 100.]
    Range    =  [180. 100.]
    Mean     =  [122.  50.]
    Variance =  [8100. 2500.]
  Graphics saved as "exercise1_two_temperatures_data.png"

  Method  ----------------c-------------     mse(r)

  Normal     [-17.77777778   0.55555556]    6.310887241768095e-30
  QR         [-17.77777778   0.55555556]    0.0
  PINV       [-17.77777778   0.55555556]    3.0923347484663663e-28
  LSTSQ      [-17.77777778   0.55555556]    2.0194839173657902e-28
  sklearn    [-17.77777778   0.55555556]    2.0194839173657902e-28
  Graphics saved as "exercise1_two_temperatures_fitted.png"

  Rescaled coefficient vectors C[0], C[1], C[2]
[160.  -5.] 8.999999999999998
[160.  -5.] 9.0
[160.  -5.] 9.000000000000014
[160.  -5.] 9.00000000000001
[160.  -5.] 9.00000000000001