Why a best-fitting line might not be

Article Abstract:

A regular data analysis procedure such as fitting a staight line to bivariate (Y vs X) normally calls for the least squares solution. However, when situations like discrepant values in data sets come up, a new approach needs to be adopted. What is being proposed is to fit a line to most of the data regardless of the small percentage of values that do not adhere to the main pattern. This represents the point that majority of the data emanates from incontrol processes, but a small percentage also comes from out-of-control behaviour.

Models, Correlation (Statistics), Least squares

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Tree-based procedures

Article Abstract:

The principles of tree-based classification are discussed. A classification tree is defined as a hierarchical set of questions on the taxonomy of an individual which allows the determination of the class which the individual belongs. Benefits of a classification tree include flexible construction, easy interpretation and application to continuous response data. Implementation of the technique in classifying plastic gears is described.

Classification, Decision tree, Decision trees

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Fitting a three-group resistant line

Article Abstract:

An alternativeto least squares in fitting a line to X-Y data is the three-group median procedure by statistician John Tukey. Tukey's method is slightly modified to fit a line to 17 X-Y pairs with an overall linear trend. Repeated iteration is applied to achieve negligible changes and residuals are obtained from intercepts until the fit is adequate.

Iterative methods (Mathematics), Usage, Iteration (Mathematics), Column, Curve fitting

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