More Information

Regression Analysis and Curve Fitting

The information on this page is provided for regression methods concerning two continuous variables (pre-defined and user-defined). For multiple-regression, partial least squares regression (PLS), or logistic regression, visit the corresponding information page using the related link on the right-hand side panel.


Regressions Concerning Two Continuous Variables (Pre-Defined)

The regression methods grouped under this title either deal with finding the relationship between one outcome (dependent) variable and one predictor (independent) variable, or finding the relationship between two variables where the designation of dependent and independent variables is irrelevant.

You can choose between 8 different methods:

      • Linear (X on Y)
      • Linear (thru zero)
      • Major axis
      • Reduced major axis
      • Polynomial
      • Exponential
      • Logarithmic
      • Power
  • Performing curve fitting on an existing chart displays the fitted curve and the regression equation(s).
  • Performing regression analysis from the Stats Analyzer provides the options of (a) displaying the X-Y plot and the defined regression curve together with the regression parameters and an ANOVA report (if applicable) in a table format displayed on the viewer page, and (b) storing the results of the analysis (i.e., the observed and predicted sequences) in an auto-generated worksheet.

Cubic Spline Interpolation

A cubic spline is made from piece-wise third-order polynomials that pass through the control points provided.

  • You can apply a cubic spline interpolation to a displayed chart, or generate a specified sequence of interpolations (using the Stats Analyzer) and save them in a worksheet for other uses.

User-Defined Non-Linear Regression

The user-defined regression uses Levenberg-Marquardt "full Newton-type" method.