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Linear Regression

The Fit Linear dialog box is used to perform linear regression and fits a straight line to a given data set. The fitting model is written as

 \begin{cases}
y=\beta _0+\beta _1x+\varepsilon \\

\varepsilon\sim\N(0,\sigma^2)
 \end{cases}

where \beta _0 \,\!is the y intercept, \beta_1 \,\!is the slope and \varepsilon is the error term. The error term represents the unexplained variation in the dependent variable and is usually assumed to have a mean of zero.

To estimate the parameters, the chi-square minimization or "weighted least-square" method is used. The goal is to minimize the sum of the squares of the deviations between the theoretical curve and the experimental points for a range of independent variables. After fitting, the model is evaluated using hypothesis tests and plotting of residuals.