The standard error estimate is computed as the square root of the mean squared error and it is a standard deviation of the errors. It is therefore useful for to making a judgment about the fit of regression model in conjunction with the assumption that the model is linear the error terms are normally distributed the error terms are independent the error terms have constant variance

The standard error estimate is computed as the square root of the mean squared error and it is a standard deviation of the errors. It is therefore useful for to making a judgment about the fit of regression model in conjunction with the assumption that the model is linear the error terms are normally distributed the error terms are independent the error terms have constant variance

Trigonometry (MindTap Course List)

8th Edition

ISBN:9781305652224

Author:Charles P. McKeague, Mark D. Turner

Publisher:Charles P. McKeague, Mark D. Turner

Chapter4: Graphing And Inverse Functions

Section: Chapter Questions

Problem 6GP: If your graphing calculator is capable of computing a least-squares sinusoidal regression model, use...

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