Linear Regression Model Assumptions
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I.
For every x, Y is normally distributed with mean A+Bx and variance σ
^{2}
.
ie, E[Y|x] or μ
_{Y|x}
=A+Bx, and v
_{(Y|x)}
=σ
^{2}
II
Y's are independently distributed
III
X's are fixed quantities, or used to predict Y-values
IV
, where
^{}
is called the variance for the error component
Card Set Information
Author:
Jamie_Bee
ID:
279930
Filename:
Linear Regression Model Assumptions
Updated:
2014-07-30 15:33:25
Tags:
StatsII
Folders:
Description:
Assumptions for using the Linear Regression Model
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