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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.
The regression equation is determined by minimizing?
The total squared error between the predicted y values and the actual y values
In a good regression model the residual plot shows?
a random pattern
What is stochastic error term?
A Stochastic error term is a term that is added to a regression equation to introduce all of the variation in Y that cannot be explained by the included Xs. It is, in effect, a symbol of the econometrician's ignorance or inability to model all the movements of the dependent variable.
How do you calculate regression equation?
what is the equation of the regression line for the given data(Age, Number of Accidents) (16, 6605), (17, 8932), (18, 8506), (19, 7349), (20, 6458), (21, 5974)
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.
The regression equation is determined by minimizing?
The total squared error between the predicted y values and the actual y values
What is the adjective of the word regression?
of, pertaining to, or determined by regression analysis: regression curve; regression equation. dictionary.com
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.
What is population regression function?
The population regression function (PRF) represents the relationship between a dependent variable and one or more independent variables in the entire population. It is typically expressed as an equation, where the dependent variable is modeled as a linear combination of the independent variables plus a random error term. The PRF aims to capture the true underlying relationship in the population, as opposed to sample estimates, which may vary due to sampling error. In practice, the PRF is often estimated using sample data through techniques like ordinary least squares regression.
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.
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 does a regression equation look like?
It can look like any algebraic equation.
What is the difference between a bias and a random error?
Bias is systematic error. Random error is not.
In a good regression model the residual plot shows?
a random pattern
