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The difference between the observed value and the estimated value in regression analysis is known as
  • a)
    Error
  • b)
    Residue
  • c)
    Deviation
  • d)
    (a) or (b)
Correct answer is option 'D'. Can you explain this answer?
Most Upvoted Answer
The difference between the observed value and the estimated value in r...
Error vs Residue in Regression Analysis

Error and residue are two terms used in regression analysis to describe the difference between the observed value and the estimated value. Let's understand the difference between them:

Error:
- Error is the difference between the observed value and the true value.
- It is usually unknown and cannot be calculated.
- It is the result of factors that are not included in the regression model.

Residue:
- Residue is the difference between the observed value and the estimated value.
- It is usually known and can be calculated.
- It is the result of factors that are included in the regression model.

Therefore, the correct answer to the question is (d) (a) or (b), as both error and residue describe the difference between the observed value and the estimated value, but they have different meanings and implications in regression analysis.
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The difference between the observed value and the estimated value in regression analysis is known asa)Errorb)Residuec)Deviationd)(a) or (b)Correct answer is option 'D'. Can you explain this answer?
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