Multiple Regression Analysis- Estimation Chapter 3 Exam Questions and Correct Answers Latest Update 2024 Already Passed
why is multiple regression analysis more amenable to ceteris paribus analysis? - Answers You can explicitly control for many other factors that simultaneously affect the depende...
why is multiple regression analysis more amenable to ceteris paribus analysis? - Answers You can
explicitly control for many other factors that simultaneously affect the dependent variable
In a multiple regression how is u related to x1 and x2? - Answers The expected value is 0. For any values
of x1 and x2 in the population the average of the unobserved factors is equal to 0.
how are the OLS estimates chosen? - Answers To minimise the sum of squared residuals
What properties do OLS fitted values have which is extension from single variables? - Answers 1) sample
average of residuals is 0
2) the sample covariance between each independent variable and the OLS residuals is 0
3) the estimated point is always on the OLS regression line
What is the Frisch Waugh theorem? - Answers the general algebraic result that provides multiple
regression analysis with its 'partialling out' interpretation
What is the explained sum of squares? - Answers The total sample variation of the fitted values in a
multiple regression model
if a independent variable is added what happens to the r2? - Answers it never decreases and will usually
increase by a little bit even if there is no effect. this makes it a poor tool for deciding whether one
variable or several variables should be added to the model.
what is an issue with a regression that is through the origin? - Answers If the intercept in the population
model is not 0 then the OLS estimators of the slope parameters will be biased
What the 4 MLR assumptions? - Answers 1) Linear in Parameters
2)Random Sampling
3) No perfect collinearity
4) Zero conditional mean
If the estimator is calculated under the 4 MLR what can we say? - Answers The OLS estimators are
unbiased estimators of the population parameters
Does using irrelevant variables affect the unbiasedness? - Answers No it does not. Using irrelevant
variables is harmless but can have undesirable effects on the variances of the OLS estimators
what is the correlation results if there is a biased estimator? - Answers if corr (x1, x2)>0
b2>0 then positive bias
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