Subscribe to DSC Newsletter

Frank Raulf's Blog – November 2019 Archive (1)

Omitted Variables in Linear Regressions

The importance of completeness of linear regressions is an often-discussed issue. By leaving out relevant variables the coefficients might be inconsistent.

But why on earth?! 

Assuming a linear complete model of the form:

z = a + bx + cy + ε.

Where z is supposed to be dependent, x and y are independent and ε is the error term.

Now we drop y to check…

Continue

Added by Frank Raulf on November 13, 2019 at 2:00am — No Comments

Videos

  • Add Videos
  • View All

© 2020   Data Science Central ®   Powered by

Badges  |  Report an Issue  |  Privacy Policy  |  Terms of Service