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Visual stats: Nonlinear curve fitting implemented to draw curves for determination of statistical values

Introduction
->> Visual Stats
->> Main Interface
   
Quick Start Tutorial
->> Functions
->> Operations
->> Parameters
->> Syntax
->> Priority Of Operations And Functions
   
Menus & Toolbar
->> File Menu
->> Edit Menu
->> Format Menu
->> Setting Menu
->> Stats Menu
->> Help Menu
->> Standard Toolbar
   
Stats
->> Probability
->> Descriptive Statistics Summary
->> Frequency Analysis
   
Compare Means
->> One Sample T Test
->> Independent-Samples T Test
->> Paired-Samples T Test
   
Compare Variables
->> One Sample
->> Two Samples
   
Variance Analysis
->> One-Way ANOVA
->> Two-Way ANOVA
   
Regression
->> Univariate Linear Regression
->> Multivariate Linear Regression
->> Curve Fitting
->> Nonlinear Curve Fitting
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Nonlinear Curve Fitting

The Main Steps Of Operation:

To implement nonlinear curve fitting, following these steps:

  1. Input your data in Data Editor.
  2. Select Stats -> Regression -> Nonlinear Curve Fitting from the menus.
  3. Select variables in Nonlinear Curve Fitting dialogbox, input model expression in Model Expression textbox, click Parameters... button to set the initial values of the parameters, and click OK button.

Note:

The maximum number of parameters Visual Stats allowed is 20. The names of parameters in Visual Stats must be one of the letters 'a' to 't' and must be priority selected alphabetically. For example, if your model has two parameters, the names of the two parameters must be 'a' and 'b'; if the model has four parameters, the names must be 'a', 'b', 'c' and 'd'.

Algorithms:

Gauss-Newton method and Levenburg-Marquardt method are provided.

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