X is Laplace
No leverage correction



Three distributions for X: Normal, uniform, Laplace

Inference for the slope in simple linear parametric regression

Actual coverage probabilities of a nominal 95% confidence interval.

Leverage corrections means we correct residuals for leverage

degrees of freedom means we correct sandwich estimator of variance by
         multiplication by n/df, and use t--percentiles with this df.

Overdispersion means the variance of the t--statistic reletive to
the variance of a t--random variable with n-2 degrees of freedom

                             Degrees of freedom         Over--    Sample 
    n       n-1       n-2     n-3      n-4      n-5   Dispersion   Size
  0.8264   0.8466   0.8680   0.8926   0.9196   0.9464    2.530    10.00 
  0.8322   0.8490   0.8696   0.8920   0.9142   0.9364    2.551    11.00 
  0.8504   0.8680   0.8844   0.9030   0.9230   0.9398    2.110    12.00 
  0.8444   0.8626   0.8788   0.8952   0.9134   0.9312    2.179    13.00 
  0.8598   0.8756   0.8894   0.9034   0.9196   0.9342    1.950    14.00 
  0.8578   0.8738   0.8862   0.8998   0.9132   0.9270    1.983    15.00 
  0.8676   0.8778   0.8876   0.9002   0.9124   0.9240    1.890    16.00 
  0.8702   0.8800   0.8920   0.9034   0.9132   0.9236    1.892    17.00 
  0.8724   0.8806   0.8894   0.8990   0.9102   0.9230    1.836    18.00 
  0.8724   0.8822   0.8906   0.9014   0.9106   0.9196    1.812    19.00 
  0.8856   0.8924   0.9004   0.9106   0.9182   0.9278    1.681    20.00 
  0.8916   0.9006   0.9072   0.9136   0.9228   0.9326    1.604    21.00 
  0.8840   0.8912   0.9002   0.9068   0.9146   0.9226    1.634    22.00 
  0.8960   0.9054   0.9122   0.9186   0.9264   0.9324    1.498    23.00 
  0.8908   0.8974   0.9078   0.9150   0.9214   0.9260    1.582    24.00 
  0.8854   0.8916   0.8990   0.9056   0.9122   0.9192    1.606    25.00 
  0.9016   0.9080   0.9130   0.9190   0.9252   0.9298    1.509    26.00 
  0.8980   0.9058   0.9100   0.9148   0.9204   0.9256    1.491    27.00 
  0.8962   0.9030   0.9066   0.9130   0.9170   0.9228    1.518    28.00 
  0.9030   0.9096   0.9150   0.9208   0.9248   0.9330    1.469    29.00 
  0.9050   0.9096   0.9128   0.9174   0.9232   0.9290    1.460    30.00