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Excel Modeling Non Linear Regression

Excel Modeling Non Linear Regression. Anchored By: Renu Rao Kaveh Saba. Features of Solver. Solver can optimize the value in the target cell by varying the adjustable cells. Cells are related by a given model equation, which is then used to find predicted values. NonLinear Regression.

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Excel Modeling Non Linear Regression

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  1. Excel ModelingNon Linear Regression Anchored By: Renu Rao Kaveh Saba

  2. Features of Solver • Solver can optimize the value in the target cell by varying the adjustable cells. • Cells are related by a given model equation, which is then used to find predicted values.

  3. NonLinear Regression • Two-variable nonlinear regression • 3 components: • Experimental Data • A model equation to follow to get predicted values • Initial guesses for variables values.

  4. In the Excel Spreadsheet… • Column 1: Independent variables from experimental data • Column 2: Values measured for the dependent variables • Column 3: Predicted values using the model equation • 2 initial guesses for variables

  5. Reaction Rate Example from Text • Given: Rate constant (k) at various temperatures (T) • Need to determine Activation Energy (E) and frequency factor (A) • Fit to Arrhenius equation • k(T) = Ae−E / RT

  6. Initial Excel Setup

  7. Thank You for viewing our presentation! Renu and Kaveh

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