This page allows performing weighted linear regressions (weighted linear least squares fittings). For the relation between two variables, it finds the linear function that best fits (giving an importance expressed by the weight to each point) a given set of data points. The exact meaning of the weights is given by the fact that in the residual sum of squares that is minimized the squares of residuals are multiplied by the weight corresponding to the row, before being summed up (i.e. a weighted sum is performed).

• Copy & Paste: You can copy and paste data directly from a spreadsheet or a tabulated data file in the box below. Any character that cannot be part of a number -space, comma, tabulation...- is considered a column separator. By default commas are considered column separators; in the case you are using them as decimal separators check the option below. The exponent can be indicated by preceding it by the character E or e, as you can see in the example. Data must consist of three columns, weight, x and y, to get the weighted linear regression y=ax+b._{ }

• Insert manually & See details: If you prefer you can insert all the points manually, for which you first have to specify the number of data points. You also can see details of the calculation -as the calculated value of y and the error at each point- in this area.