3.107 FAQ-645 What kind of Fit Statistics can be obtained in linear fit?

Last Update: 9/10/2019

Linear Regression perform statistics for fitting results, the main statistics values were introduced below:

  • Number of Points
    Total number of fitting points.
  • Degrees of Freedom
    Model degrees of freedom.
  • Reduced Chi-Sqr
    The Reduced Chi-square value (equal to the residual sum of square divided by the degrees of freedom).
  • R Value
    The R\,\! value (equal to to square root of R^2\,\!).
  • Residual Sum of Squares
    Residual sum of squares (RSS); or sum of square error.
  • Pearson's r
    Pearson correlation coefficient.
  • R-Square (COD)
    Coefficient of determination.
  • Adj. R-Square
    Adjusted coefficient of determination.
  • Root-MSE (SD)
    Residual standard deviation; or square root of mean square error.
  • Norm of Residuals
    Norm of residuals; equals to square root of RSS.
    For more information, see Statistics
    Output the analysis of variance table.
    For more information, see: ANOVA Table
  • Covariance matrix
    Output the covariance matrix.
    For more information, see: Covariance and Correlation Matrix
  • Correlation matrix
    Output the correlation matrix.
    For more information, see: Covariance and Correlation Matrix
  • Outliers
    Output the outliers list.

    To further learn about how to interprete these statistics after fit, please refer to the document:Interpreting Regression Results

    Keywords:Fit Statistics, Linear Curve Fit