Regression - Cannot force a zero intercept Only fits linear...

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Regression
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A common engineering task is to fit experimental data to a mathematical model. Often the model is simply a fit to a straight line. Other times the model may be quite complex. Excel has several tools to fit models to data.
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Consider the following data. What is the best linear fit? The fit that minimizes error (best fit) can be obtained using statistical arguments.
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There are several methods for modeling trends to data in Excel. Each has its own strengths and weaknesses. Builtin functions for linear fit: Slope(y,x) Intercept(y,x) rsq(y,x) Advantages: Updates when data is changed Results are easily used in further calculations Disadvantages:
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Unformatted text preview: Cannot force a zero intercept Only fits linear data Trendline Fit with Chart Tool Fits several linear regression models besides y=ax+b (see Larsen pp. 160-162) Advantages: Updates when data is changed Multiple model types. Can force model through defined intercept Disadvantages: Equation is not directly transferable to calculations Data Analysis/Regression Fits models of the type: y(x) = A f 1 (x) + B f 2 (x) + Advantages: Very flexible model types. Can force model through origin Results are useable in further calculations Disadvantages: Fit does not update when original data is changed Must re-run analysis...
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Regression - Cannot force a zero intercept Only fits linear...

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