The deterministic component: B0 + B1X; can be thought of as the expected
value of Y given X, the mean value of the Ys associated with a particular
value of X.
The stochastic error term must be present in a regression equation because
there are at least four sources of variation in Y other than the variation in
the included Xs:
1. Many minor influences on Y are omitted from the equation (for
example, because data are unavailable).
2. It is virtually impossible to avoid some sort of measurement
error in at least one of the equation’s variables.
3. The underlying theoretical equation might have a different
functional form than the one chosen for the regression. For
example, the underlying equation might be nonlinear in the
variables for a linear regression.
4. All attempts to generalize human behavior must contain at least
some amount of unpredictable or purely random variation.
Extending the notation
The meaning of the regression coefficient beta-one: the impact of a one
unit increase in X-one on the dependent variable Y, holding constant the
other included independent variables.
Multivariate regression coefficients: serve to isolate the impact on Y of a
change in one variable from the impact on y of the changes in the other
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