class: center, middle, inverse, title-slide # Midterm Review Questions ## ECON 480 · Econometrics · Fall 2019 ### Ryan Safner
Assistant Professor of Economics
safner@hood.edu
ryansafner/metricsf19
metricsF19.classes.ryansafner.com
--- # Question 1 What does **endogenous** mean, in words? What about statistically? --- # Question 2 If a regression is biased (from endogeneity), what can we learn about the bias? --- # Question 3 What does heteroskedasticity mean? Does heteroskedasticity **bias** `\(\hat{\beta_1}\)`? --- # Question 4 Is this data likely heteroskedastic or homoskedastic? <!-- --> --- # Question 5 - What three things impact the variation of `\(\hat{\beta_1}\)`? How? --- # Question 6 What are the four assumptions we make about the error term? Which is most important? --- # Question 7 `$$Wages_i=\hat{\beta_0}+\hat{\beta_1}Education+u_i$$` What is in `\(u_i\)`? Is `\(\hat{\beta_1}\)` likely biased? --- # Question 8 What does `\(R^2\)` measure? What does it mean? How do we calculate it? --- # Question 9 What does `\(\sigma_u\)` (SER) measure? What does it mean? --- # Question 10 Interpret all of these numbers (except Adjusted R-squared and the last line): ``` ## ## Call: ## lm(formula = y ~ x, data = het_data) ## ## Residuals: ## Min 1Q Median 3Q Max ## -5.2447 -0.5159 0.0207 0.4802 5.5260 ## ## Coefficients: ## Estimate Std. Error t value Pr(>|t|) ## (Intercept) -0.02432 0.10617 -0.229 0.819 ## x 1.05812 0.09219 11.478 <2e-16 *** ## --- ## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 ## ## Residual standard error: 1.149 on 498 degrees of freedom ## Multiple R-squared: 0.2092, Adjusted R-squared: 0.2076 ## F-statistic: 131.7 on 1 and 498 DF, p-value: < 2.2e-16 ``` --- # Question 11 Interpret all of these numbers:
(1)
(Intercept)
-0.024
(0.106)
x
1.058 ***
(0.092)
N
500
R-Squared
0.209
SER
1.149
*** p < 0.001; ** p < 0.01; * p < 0.05.
--- # Question 12 Suppose `\(Y\)` is normally distributed with a mean of 10 and a standard error of 5. What is the probability that `\(Y\)` is between 5 and 15? --- # Question 13 Explain what a `\(Z\)`-score means. --- # Question 14 Explain what a `\(p\)`-value means. :) --- # Question 15 We run the following hypothesis test at `\(\alpha=0.05\)`: `$$\begin{align*} H_0: \, & \beta_1=0\\ H_1: \, & \beta_1 \neq 0 \\ \end{align*}$$` Is this test one-sided or two-sided? We find the `\(p\)`-value is 0.02. What is our conclusion? Be specific and precise in your wording!