Tools

Regression and curve fitting using procedures such as Least-Square and Weighted Least-Square curve fitting.

Procedure:

  1. Data Collection
  • Prepare experimental data points (x, y coordinates)
  • Ensure at least 2 data points are available
  • Optional: Prepare corresponding weight values for weighted regression.
  1. Input Data
  • Enter x,y data points in the "Enter X,Y Data Points" textarea
  • Format: One coordinate pair per line, separated by comma
  • Example: 1,2.1 2,4.0 3,6.3 4,8.1 5,9.9
  • Optional: Enter weights in corresponding textarea
  1. Configure Regression Parameters
  • Select desired regression type from dropdown: a. Linear Regression b. Polynomial (2nd degree) c. Exponential Regression
  1. Perform Analysis
  • Click "Simulate" button
  • Observe results in Results column:
    • Regression equation
    • R-squared value
    • Graphical plot of data points and regression line
  1. Data Interpretation
  • Analyze regression equation coefficients
  • Evaluate R-squared value (goodness of fit)
  • Compare different regression models
  • Draw conclusions about data relationship

Caution:

  • Ensure numeric data entry
  • Provide sufficient data points for meaningful regression