Suppose the first assumption is replaced with E(u;X;) = 2. What happens to E(Y,IX;)? O A. The slope B₁ changes to B₁ +2. OB. Nothing changes. O C. Both the intercept and the slope ₁ change to Bo +2 and ₁ + 2 respectively. OD. The intercepto changes to Bo +2. Are the rest of the OLS assumptions satisfied? O A. Both OLS assumptions (2) and (3) are satisfied. OB. OLS assumption (3) is satisfied but not (2). O C. Neither OLS assumption (2) nor (3) is satisfied. O D. OLS assumption (2) is satisfied but not (3).
Suppose the first assumption is replaced with E(u;X;) = 2. What happens to E(Y,IX;)? O A. The slope B₁ changes to B₁ +2. OB. Nothing changes. O C. Both the intercept and the slope ₁ change to Bo +2 and ₁ + 2 respectively. OD. The intercepto changes to Bo +2. Are the rest of the OLS assumptions satisfied? O A. Both OLS assumptions (2) and (3) are satisfied. OB. OLS assumption (3) is satisfied but not (2). O C. Neither OLS assumption (2) nor (3) is satisfied. O D. OLS assumption (2) is satisfied but not (3).
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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![**The Least Squares Assumptions**
1. The error term \( u_i \) has conditional mean zero given \( X_i \): \( E(u_i|X_i) = 0 \);
2. \( (X_i, \, Y_i) \), \( i = 1, \ldots, n \), are independent and identically distributed (i.i.d.) draws from their joint distribution; and
3. Large outliers are unlikely: \( X_i \) and \( Y_i \) have nonzero finite fourth moments.
\[ Y_i = \beta_0 + \beta_1 X_i + u_i, \, i = 1, \ldots, n, \text{ where} \]
Suppose the first assumption is replaced with \( E(u_i|X_i) = 2 \). What happens to \( E(Y_i|X_i) \)?
- **A.** The slope \( \beta_1 \) changes to \( \beta_1 + 2 \).
- **B.** Nothing changes.
- **C.** Both the intercept \( \beta_0 \) and the slope \( \beta_1 \) change to \( \beta_0 + 2 \) and \( \beta_1 + 2 \) respectively.
- **D.** The intercept \( \beta_0 \) changes to \( \beta_0 + 2 \).
Are the rest of the OLS assumptions satisfied?
- **A.** Both OLS assumptions (2) and (3) are satisfied.
- **B.** OLS assumption (3) is satisfied but not (2).
- **C.** Neither OLS assumption (2) nor (3) is satisfied.
- **D.** OLS assumption (2) is satisfied but not (3).](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fe28c09e6-8851-4dc8-bd0a-e2da2822035b%2F86d5e4f0-ff75-49aa-a555-afdf6419b497%2Fne4h7w9_processed.png&w=3840&q=75)
Transcribed Image Text:**The Least Squares Assumptions**
1. The error term \( u_i \) has conditional mean zero given \( X_i \): \( E(u_i|X_i) = 0 \);
2. \( (X_i, \, Y_i) \), \( i = 1, \ldots, n \), are independent and identically distributed (i.i.d.) draws from their joint distribution; and
3. Large outliers are unlikely: \( X_i \) and \( Y_i \) have nonzero finite fourth moments.
\[ Y_i = \beta_0 + \beta_1 X_i + u_i, \, i = 1, \ldots, n, \text{ where} \]
Suppose the first assumption is replaced with \( E(u_i|X_i) = 2 \). What happens to \( E(Y_i|X_i) \)?
- **A.** The slope \( \beta_1 \) changes to \( \beta_1 + 2 \).
- **B.** Nothing changes.
- **C.** Both the intercept \( \beta_0 \) and the slope \( \beta_1 \) change to \( \beta_0 + 2 \) and \( \beta_1 + 2 \) respectively.
- **D.** The intercept \( \beta_0 \) changes to \( \beta_0 + 2 \).
Are the rest of the OLS assumptions satisfied?
- **A.** Both OLS assumptions (2) and (3) are satisfied.
- **B.** OLS assumption (3) is satisfied but not (2).
- **C.** Neither OLS assumption (2) nor (3) is satisfied.
- **D.** OLS assumption (2) is satisfied but not (3).
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