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

A First Course in Probability (10th Edition)
10th Edition
ISBN:9780134753119
Author:Sheldon Ross
Publisher:Sheldon Ross
Chapter1: Combinatorial Analysis
Section: Chapter Questions
Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...
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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
Transcribed Image Text: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
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