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 1, where Image Upload 2 is called the variance for the error component
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279930
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Linear Regression Model Assumptions
Description
Assumptions for using the Linear Regression Model
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