     @data.x = x_new
     @data.y = y_new
 
-    # # normalize
-    # for yValue in [ @data.y... ]
-    #   yValue = (+yValue-@smallestY)/(@largestY-@smallestY)
-
   std: (data) ->
     mean = @mean(data)
     sum = 0

    @smallestY = Math.min @data.y...
    @largestX = Math.max  @data.x...
    @largestY = Math.max  @data.y...

  disableMarking: ->
    @markingDisabled = true


    # remove outliers and normalize
    @removeOutliers(3)
    @data.y = @normalize(@data.y)





    # # normalize
    # yNorm = []
    # yMin = Math.min @data.y...
    # yMax = Math.max @data.y...
    # for yValue, i in [ @data.y... ]
    #   yNorm[i] = (+yValue-yMin)/(yMax-yMin)
    # @data.y = yNorm


    # normalize y values to unity mean
    yMean = @mean(@data.y)
    console.log 'yMean: ', yMean

    # for yValue, i in [ @data.y... ]
    #   @data.y[i] =  (@data.y[i]-@smallestY) / (@largestY-@smallestY)
      # console.log 'y: ', @data.y[i]

    # for yValue, i in [ @data.y... ]
