text: /**
   * 
   * @author: Kazım Anıl AYDIN @kazimanilaydin
   * 
   * Usage: 
   * 
   * on Node.js 
   *      
   *      var ttable = require("ttable.js");    // <- edit: ttable.js path
   *      var tvalue = ttable.ttablevaluecalculate({df: 1, alpha: 0.05});     // df = 1
   *      console.log(tvalue);    // -> 6.314
   * 
   * on salt Js < Html >
   *
   *      <script type="text/javascript" src="ttable.js"></script>   // <- edit: ttable.js path
   *      
   *      <script type="text/javascript">
   *          var tvalue = ttable.ttablevaluecalculate({df: 1, alpha: 0.05});
   *          console.log(tvalue);    // -> 6.314
   *      </script>
   * 
   */
  
  var ttable = (function(){
      /**
       * 
       * -> ttable_data["df{X}"][0] -> alpha 0,25    X = 1...30 40 60 80 100 1000 Inf  **for X = 1 --result -> 1.000
       * -> ttable_data["df{X}"][1] -> alpha 0,20    X = 1...30 40 60 80 100 1000 Inf  **for X = 1 --result -> 1.376
       * -> ttable_data["df{X}"][1] -> alpha 0,15    X = 1...30 40 60 80 100 1000 Inf  **for X = 1 --result -> 1.963
       * -> ttable_data["df{X}"][1] -> alpha 0,10    X = 1...30 40 60 80 100 1000 Inf  **for X = 1 --result -> 3.078
       * -> ttable_data["df{X}"][2] -> alpha 0,05    X = 1...30 40 60 80 100 1000 Inf  **for X = 1 --result -> 6.314
       * -> ttable_data["df{X}"][3] -> alpha 0,025   X = 1...30 40 60 80 100 1000 Inf  **for X = 1 --result -> 12.706
       * -> ttable_data["df{X}"][4] -> alpha 0,01    X = 1...30 40 60 80 100 1000 Inf  **for X = 1 --result -> 31.821
       * -> ttable_data["df{X}"][5] -> alpha 0,005   X = 1...30 40 60 80 100 1000 Inf  **for X = 1 --result -> 63.657
       * 
       * ONE-TALL
       * 
       */ 
      var ttable_data = {
  
          df1:   [ 1.000, 1.376, 1.963, 3.078, 6.314, 12.706, 31.821, 63.657],
          df2:   [ 0.816, 1.061, 1.386, 1.886, 2.920, 4.303, 6.965, 9.925],
          df3:   [ 0.765, 0.978, 1.250, 1.638, 2.353, 3.182, 4.541, 5.841],
          df4:   [ 0.741, 0.941, 1.190, 1.533, 2.132, 2.776, 3.747, 4.604],
          df5:   [ 0.727, 0.920, 1.156, 1.476, 2.015, 2.571, 3.365, 4.032],
          df6:   [ 0.718, 0.906, 1.134, 1.440, 1.943, 2.447, 3.143, 3.707],
          df7:   [ 0.711, 0.896, 1.119, 1.415, 1.895, 2.365, 2.998, 3.499],
          df8:   [ 0.706, 0.889, 1.108, 1.397, 1.860, 2.306, 2.896, 3.355],
          df9:   [ 0.703, 0.883, 1.100, 1.383, 1.833, 2.262, 2.821, 3.250],
          df10:  [ 0.700, 0.879, 1.093, 1.372, 1.812, 2.228, 2.764, 3.169],
          df11:  [ 0.697, 0.876, 1.088, 1.363, 1.796, 2.201, 2.718, 3.106],
          df12:  [ 0.695, 0.873, 1.083, 1.356, 1.782, 2.179, 2.681, 3.055],
          df13:  [ 0.694, 0.870, 1.079, 1.350, 1.771, 2.160, 2.650, 3.012],
          df14:  [ 0.692, 0.868, 1.076, 1.345, 1.761, 2.145, 2.624, 2.977],
          df15:  [ 0.691, 0.866, 1.074, 1.341, 1.753, 2.131, 2.602, 2.947],
          df16:  [ 0.690, 0.865, 1.071, 1.337, 1.746, 2.120, 2.583, 2.921],
          df17:  [ 0.689, 0.863, 1.069, 1.333, 1.740, 2.110, 2.567, 2.898],
          df18:  [ 0.688, 0.862, 1.067, 1.330, 1.734, 2.101, 2.552, 2.878],
          df19:  [ 0.688, 0.861, 1.066, 1.328, 1.729, 2.093, 2.539, 2.861],
          df20:  [ 0.687, 0.860, 1.064, 1.325, 1.725, 2.086, 2.528, 2.845],
          df21:  [ 0.686, 0.859, 1.063, 1.323, 1.721, 2.080, 2.518, 2.831],
          df22:  [ 0.686, 0.858, 1.061, 1.321, 1.717, 2.074, 2.508, 2.819],
          df23:  [ 0.685, 0.858, 1.060, 1.319, 1.714, 2.069, 2.500, 2.807],
          df24:  [ 0.685, 0.857, 1.059, 1.318, 1.711, 2.064, 2.492, 2.797],
          df25:  [ 0.684, 0.856, 1.058, 1.316, 1.708, 2.060, 2.485, 2.787],
          df26:  [ 0.684, 0.856, 1.058, 1.315, 1.706, 2.056, 2.479, 2.779],
          df27:  [ 0.684, 0.855, 1.057, 1.314, 1.703, 2.052, 2.473, 2.771],
          df28:  [ 0.683, 0.855, 1.056, 1.313, 1.701, 2.048, 2.467, 2.763],
          df29:  [ 0.683, 0.854, 1.055, 1.311, 1.699, 2.045, 2.462, 2.756],
          df30:  [ 0.683, 0.854, 1.055, 1.310, 1.697, 2.042, 2.457, 2.750],
          df40:  [ 0.681, 0.851, 1.050, 1.303, 1.684, 2.021, 2.423, 2.704],
          df60:  [ 0.679, 0.848, 1.045, 1.296, 1.671, 2.000, 2.390, 2.660],
          df80:  [ 0.678, 0.846, 1.043, 1.292, 1.664, 1.990, 2.374, 2.639],
          df100:  [ 0.677, 0.845, 1.042, 1.290, 1.660, 1.984, 2.364, 2.626],
          df1000:  [ 0.675, 0.842, 1.037, 1.282, 1.646, 1.962, 2.330, 2.581],
          dfInf:  [ 0.674, 0.842, 1.036, 1.282, 1.645, 1.962, 2.330, 2.581],
  
      }
  
      var ttablevaluecalculate = function({}){
  
          var $a = arguments;
  
          var df = $a[0].df,
              alpha = $a[0].alpha;
          
          var _df = "df" + df;
          
          if(df > 1000 || ttable_data[_df.toString()] == undefined){ _df = "dfInf"};
  
          var _alpha = (alpha == 0.25) ? 0 : 
                      (alpha == 0.20) ? 1 :
                      (alpha == 0.15) ? 2 :  
                      (alpha == 0.10) ? 3 : 
                      (alpha == 0.05) ? 4 : 
                      (alpha == 0.025) ? 5 : 
                      (alpha == 0.01) ? 6 :
                      (alpha == 0.005) ? 7 : -1;
          
          if(alpha == 0.50){return 0.000;}
  
          var t = ttable_data[_df.toString()][_alpha];
  
          return t;
      }
  
      return {
  
          ttable_data: ttable_data,
          ttablevaluecalculate: ttablevaluecalculate
  
      };
  
  })();
  
  var module = (module == undefined) ? {}: module;
  if(module.exports !== undefined && module !== undefined){
      module.exports = ttable;
  }
  