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includes both positive and negative terms.

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2011-09-26 00:54:03
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Q: The random error in a regression equation?
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Is the random error in a regression equation the predicted error?

pig benis


What are the sources of error in regression model?

Random error, measurement error, mis-specification of model (overspecification or underspecification), non-normality, plus many more.


What is the role of the stochastic error term in regression analysis?

Regression analysis is based on the assumption that the dependent variable is distributed according some function of the independent variables together with independent identically distributed random errors. If the error terms were not stochastic then some of the properties of the regression analysis are not valid.


What is the adjective of the word regression?

of, pertaining to, or determined by regression analysis: regression curve; regression equation. dictionary.com


The regression equation is determined by minimizing?

The total squared error between the predicted y values and the actual y values


What is the only condition under which (x y) regression equation solved for x gives the same predictions as the (y x) regression equation?

If the regression is a perfect fit.


A trend equation is a regression equation in which?

the independent variable is time


What is regression coefficient and correlation coefficient?

The strength of the linear relationship between the two variables in the regression equation is the correlation coefficient, r, and is always a value between -1 and 1, inclusive. The regression coefficient is the slope of the line of the regression equation.


What does a regression equation look like?

It can look like any algebraic equation.


Given a linear regression equation of equals 20 - 1.5x where will the point 3 15.5 fall with respect to the regression line?

on the lineGiven a linear regression equation of = 20 - 1.5x, where will the point (3, 15) fall with respect to the regression line?Below the line


What is the difference between the stochastic error term and the residual?

the residual is the difference between the observed Y and the estimated regression line(Y), while the error term is the difference between the observed Y and the true regression equation (the expected value of Y). Error term is theoretical concept that can never be observed, but the residual is a real-world value that is calculated for each observation every time a regression is run. The reidual can be thought of as an estimate of the error term, and e could have been denoted as ^e.


What is the difference between a bias and a random error?

Bias is systematic error. Random error is not.

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