Best Answer · By JanBask Data Science Expert
Jiten Miglani JanBask Expert
Answered on Jan 15, 2020
Linear regression has the following assumptions, failing which the linear regression model
does not hold true:
The dependent variable should be a linear combination of independent variables
There should not be any autocorrelation in error terms
The errors should have zero mean and should be normally distributed
There should not be any multi-col linearity between the variables
Error terms should be homeostatic in nature
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