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Explain what is meant by an error term. What assumptions do we make
about an error term when estimating an ordinary least squares regression?
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- When running a ols regression, if my control variables are insignificant via T-test should I keep them in the regression? Are they significant?Distinguish between the R2 and the standard error of a regression. How doeach of these measures describe the fit of a regression?What do you mean by the Sampling Distribution of the OLS Estimators in Multiple Regression?
- Consider the IV regression model Yi = β0 + β1Xi + β2Wi + ui, where Xi is correlated with ui and Zi is an instrument. Suppose that the first three assumptions in Key Concept (The IV Regression Assumptions) are satisfied. Which IV assumption is not satisfied whena) Zi is independent of (Yi, Xi, Wi)?b) Zi=Wi?c) Wi is1 for all i?d) Zi=Xi?What is a linear regression model? What is measured by the coefficients ofa linear regression model? What is the ordinary least squares estimator?Past class data has shown that the regression line relating the final exam score and the midterm exam score for students who take statistics from the College of Information Technology and Engineering from Dr. Kalaw is: final exam = 50 + 0.5 × midterm One interpretation of the slope is a. students only receive half as much credit (.5) for a correct answer on the final exam compared to a correct answer on the midterm exam. b. a student who scored 0 on the midterm would be predicted to score 50 on the final exam. c. a student who scored 10 points higher than another student on the midterm would be predicted to score 5 points higher than the other student on the final exam. d. a student who scored 0 on the final exam would be predicted to score 50 on the midterm exam.
- Consider the regression model Yi = β0 + β1X1i + β2X2i + ui. Transform the regression so that you can use a t-statistic to testa) β1=β2.b) β1+aβ2=0.c) β1 + β2 = 1.Consider the regression model Yi = b0 + b1X1i + b2X2i + ui. Use approach 2from Section 7.3 to transform the regression so that you can use a t-statistic to testa. b1 = b2.b. b1 + 2b2 = 0.c. b1 + b2 = 1. (Hint: You must redefine the dependent variable in theregression.)Consider the regression model Yi = β0 + β1Xi + ui.a. Suppose you know that β0 = 0. Derive a formula for the least squaresestimator of β1.b. Suppose you know that β0 = 4. Derive a formula for the least squaresestimator of β1?