Linear Regression Model Assumptions

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  1. I.
    For every x, Y is normally distributed with mean A+Bx and variance σ2 .

    ie, E[Y|x] or μY|x =A+Bx, and v(Y|x)2
  2. II
    Y's are independently distributed
  3. III
    X's are fixed quantities, or used to predict Y-values
  4. IV
    Image Upload, where Image Upload 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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