Help please will give 5 stars and amazing feedback! TRUE OR FALSE AND WHY???
Here first I wrote the answer i.e. True or False and then have given the justification in both the questions.
First one a theorem on conditional expectation of bivariate distribution function and the second one is on the reproductive property of normal distribution.
Help please will give 5 stars and amazing feedback! TRUE OR FALSE AND WHY??? (g) Suppose...
Help please will give 5 stars and amazing feedback! TRUE OR FALSE AND WHY??? (a) Suppose that X is normally distributed with mean 0 and variance 1. Then 3. X is normally distributed with mean 0 and variance 9 True False b) The CLT states that, in large enough samples, the sample average is close to the true ex- pected value with very high probability. True False (c) The assumption that E(ui| X) 0 implies that Cov(ui, Xi)0. True False
Please help, 5 stars and a great comment right away!!! (g) E(Xi | Y) = 1 implies that Cov(X,K) = 0. True False (h) Suppose that Xi,... , Xio are independent normal random variables with mean 1 and vari- ance l. Then Σί01 Xi is normally distributed with mean 10 and variance 10. True euc False
Help please will give 5 stars and amazing feedback! TRUE OR FALSE AND WHY???
Help please will give 5 stars and amazing feedback! STEPS BY STEPS Let Y53X, uiwhere X, ~N,1) and ui~ N(0, 1) are independent and 1, 1) and u ~ suppose that you have an i.id. sample of observations (X,,K),i-1,. . . , п. (b) Show that EBo]8.
Help please will give 5 stars and amazing feedback! STEP BY STEPS Let = 5+3Xitu; where Xi ~ N(1,1) and ui ~ N(0,1) are independent and suppose that you have an i.id, sample of observations (X,Y),јн 1, , п. (a) Suppose you run a regression of Y on a constant, omitting X: o-arg min > (Y,-b i-1 Show that Bo Y
Help please will give 5 stars and amazing feedback! STEPS BY STEPS Let Y53X, uiwhere X, ~N,1) and ui~ N(0, 1) are independent and 1, 1) and u ~ suppose that you have an i.id. sample of observations (X,,K),i-1,. . . , п. (c) Show that β〉, 3, where A is the standard OLS estimator from a regression 01% on X., including a constant Hint: You can use the tollowing result from the lecture without proof: Var(%)
Please help!! 5 stars please step by steps and ill leave an amazing comment asap (s) Under the standard OLS asumptions, the estimator jbtained from a regression of y, on X, without a constant is consistent ifAo=0 O True O False (h) Suppose that X, N(0,1) and that X,, i-1,..,n are i.id. Then Vn( -0) is well-approximated by a normal distribution
State whether the following is always true (T) or not always true (F) a)V (4X − 2Y ) = 16V (X) + 4V (Y ) + 8Cov(X, Y ) b)If X1, X2, ..., X100 are independent, normally distributed random variables, then the average X¯ = 1 100Σ 100 i=1Xi of these random variables is itself a random variable following a normal distribution. c) If X and Y are random variables with a correlation of ρxy, Corr(2X, Y ) = 2ρxy
Please help!! 5 stars please step by steps and ill leave an amazing comment asap (e) A 95% confidence interval for A can be computed as [A-1 .96-Var(31), A + 1.96 Var (A)] O True O False (f) Suppose you run a regression of health status (Y) on a binary indicator for whether and individual has health insurance (X). Assuming that the sample is i.i.d. and that large outliers are unlikely, the coefficient has a descriptive interpretation. O True O...
5. Suppose X is a normally distributed random variable with mean μ and variance 2. Consider a new random variable, W=2X + 3. i. What is E(W)? ii. What is Var(W)? 6. Suppose the random variables X and Y are jointly distributed. Define a new random variable, W=2X+3Y. i. What is Var(W)? ii. What is Var(W) if X and Y are independent?