- You can display a label of x, y and z axis, and an explanatory note (legend) in a graph.

- When you select in order of "Edit"->"Copy" in the menu bar of the graph display, the graph image can be copied onto the clipboard.
- Next, when starting the
**Paint**and selecting from the menu bar of the Paint in order of "Edit(E)"->"Putting (P)", the image is put on the Paint. - The graph image can be preserved by a suitable file format (
**jpeg**and**png**, etc.) when you select from the menu bar of the Paint in order of "File (F)"->"Preserve it giving a name (A)".

- When you select in order of "Edit"->"Copy" in the menu bar of the graph display, the graph image can be copied onto the clipboard.
- Next, when starting
the
**Preview**and selecting from the menu bar of the Preview in order of "File"->"New make from the clipboard", the image is put on the Preview. - The graph image can be preserved by a suitable file format
(
**jpeg**and**png**, etc.) when you select from the menu bar of the Preview in order of "File"->"Preserve it by the alias".

- When you select in order of "Edit"->"Copy" in the menu bar of the graph display, the graph image can be copied onto the clipboard.
- Next, start the
**OpenOffice**, and select**graphic depiction (B)**. - Select from the menu bar in order of "Edit"->"Putting (P)", and put the image.
- The graph image can be preserved by a suitable file format
(
**png**and**eps**, etc.) when you select from the menu bar in order of "File"->"Export (T)".

- The "correction norm" is the value of the norm of the correction
vector. It is the value of the norm , where
*(i=1,2,...,m)*is the elements of the correction vector which corrects the parameter*p*._{i}(i=1,2,...,m) - The "damping factor" is the value of the additional factor of the diagonal elements in the curvature matrix in the normal equation in (Levenberg-)Marquardt method. The value of the is desirable to be 0. If the value of the is not 0, adjust the initial values of the parameters and try to fit again.
- The "probability" shows the probability in the chi-square distribution that the value of the chi-square exceeds the observed chi-square for a correct model.
- The residual is defined as the difference between the observed
value
*y*and the function value_{i}*f(x*corresponding to_{i})*x*value for the observed value, . The sum of the suqared residuals(SSR) is also defined as . - The "root mean square(RMS)" is defined as the square root of the sum of the squared residuals(SSR) divided by the number of degrees of freedom(ndf), . This is a measure of the standard deviation of the residuals.

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