b) This is not the mathematical representation of consistency of the estimator hat. A mathematical representation of consistency of the estimator hat would be as follows:
An estimator of θ (let's say Tn) is consistent if it converges in probability to θ. Then,
plim n→∞ Tn=θ
Convergence in probability, mathematically, means
lim n→∞ P( |Tn−θ| ≥ ϵ)=0 for all ϵ>0
Consider the regression equation Y = Bo+B1Xi+u; where E[u;|Xi]=0 for all i = 1, ..., n....
1. Suppose that Yi = Bo + B1Xi + €¡ where ; is N(0,0.6), Bo = 2 and 31 = 1. (a) What are the conditional mean and standard deviation of Yị given that Xi = 1? What is P(Yi < 3|X; = 1)? (b) A regression model is a model for the conditional distribution of Yị given Xị. However, if we also have a model for the marginal distribution of X; then we can find the marginal distribution of...
We consider the regression model Y=Bo + B1X + u sample size of n =946 And we found for a Y=4.75 -0.1748 (0.94) (0.1840) Give the p-value for the test Ho:B1 0 H1:B1 0 (round your answer to 4 digits after the decimal). QUESTION 16 We consider the regression model Y Bo+ B1X u And we found for a sample size of n = 946 Y= 6.318 + 0.24462 (0.44) (0.1620) Give the p-value for the test Ho:B1 0 H1:B1...
Question 1 Consider the simple regression model (only one covariate): y= BoB1 u Let B1 be the OLS estimator of B1. a) What are the six assumptions needed for B1 to be unbiased, have a simple expression for its variance, and have normal distribution? (3 points) b) Under Assumptions 1-6, derive the distribution of B1 conditional on x\,..., xn. (3 points) In lecture we described how to test the null hypothesis B1 bo against the alternative hypothesis B1 bo, where...
Exercise 4.11 Consider the regression model Y Po PX+u Suppose that you know Bo 1. Derive the formula for the least squares estimator of p The least squares objective function is OA. n (v2-bo-bx?) i-1 Ов. O B. n (M-bo-bX) /# 1 n Click to select your answer and then click Check Answer. Exercise 4.11 OA n Σ (--B,χ?) O B. E (Y-bo-b,X)2 j= 1 n Σ (Υ-Βo-bΧ) 3. j= 1 D. n Σ (Υ-0-b,) i- 1 Click to select...
Type or pas 2. Let the population regression model between a dependent variable y and an independent variable is given by y= Bo+ B1 x x+ u Suppose that E(u|x) = E(u) = 0 and V(ux) = o2. Based on a random sample ((y, ) i = 1,2,...n) of size n such that (xi- )2>0, let Bo and B be the OLS estimates of Bo and Bi respectively. Answer the following questions (c) Let B i Show that if B1...
QUESTION 1 We consider the regression model Y= Bo+B1X u And we found for a sample size of n 974 B1 -0.095 and S 0.02 Does X has a significant effect on Y at the 5 % level? True False
2. Consider the simple linear regression model: where e1, .. . , es, are i.i.d. N (0, o2), for i= 1,2,... , n. Suppose that we would like to estimate the mean response at x = x*, that is we want to estimate lyx=* = Bo + B1 x*. The least squares estimator for /uyx* is = bo bi x*, where bo, b1 are the least squares estimators for Bo, Bi. ayx= (a) Show that the least squares estimator for...
3. Consider the multiple linear regression model iid where Xi, . . . ,Xp-1 ,i are observed covariate values for observation i, and Ei ~N(0,ơ2) (a) What is the interpretation of B1 in this model? (b) Write the matrix form of the model. Label the response vector, design matrix, coefficient vector, and error vector, and specify the dimensions and elements for each. (c) Write the likelihood, log-likelihood, and in matrix form. aB (d) Solve : 0 for β, the MLE...
QUESTION 1 Consider the following OLS regression line (or sample regression function): wage =-2.10+ 0.50 educ (1), where wage is hourly wage, measured in dollars, and educ years of formal education. According to (1), a person with no education has a predicted hourly wage of [wagehat] dollars. (NOTE: Write your answer in number format, with 2 decimal places of precision level; do not write your answer as a fraction. Add a leading minus sign symbol, a leading zero and trailing...
1. Given data on (yi, xi) for i = 1, , n, consider the following least square problem for a imple linear regression bo,b We assume the four linear regression model assumptions dicussed in class hold (i) Compute the partial derivatives of the objective function. (ii) Put the derived partial derivatives in (i) equal to zeros. Explain why the resulting equa tions are called normal equation'. (Hin wo n-dimesional vectors (viand (wi)- are normal-orthogonal ) if Σ-1 ui wi-0. )...