Help please will give 5 stars and amazing feedback! TRUE OR FALSE AND WHY???
(a)
If X ~ Normal ( 0 , 1 )
Then,
Mean of X = E(X) = 0
Variance of X = Var(X) = 1
Now, For any constant 'a'
We have property as :
E(aX) = a*E(X)
Var(aX) = a2 * Var(X)
Mean of 3X = E(3X) = 3*E(X) = 3*0 = 0
Variance of 3X = Var(3X) = 32 * Var(X) = 9*1 = 9
So, 3X is normally distributed with mean 0 and variance 9
Hence, This statement is TRUE
(b)
The Central Limit Theorem states that the sampling distribution of the sample means approaches a normal distribution as the sample size gets larger. An essential component of the Central Limit Theorem is that the average of your sample means will be the population mean ( True expected value ).
Hence, this statement is TRUE
(c)
Using Law of Iterated expectations :
Now,
Hence, This statement is FALSE
Help please will give 5 stars and amazing feedback! TRUE OR FALSE AND WHY??? (a) Suppose...
Help please will give 5 stars and amazing feedback! TRUE OR FALSE AND WHY??? (g) Suppose that E(Y | X) 1+2x and that E(X)-2. Then E(Y) 5 True False (h) Suppose that X1 and X2 are independent normal random variables with mean 0 and vari- ance 1. Then (X1 + X2)/2 is normally distributed with mean 0 and variance 1 True False
Help please will give 5 stars and amazing feedback! TRUE OR FALSE AND WHY???
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! 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 (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...
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
True or False: Given the necessary assumption: E(u|X) = 0, β ̂ is a random variable with a distribution centered at 0. Given the necessary assumption: E(u|X) =0, β ̂ is a random variable with a distribution centered at β. Adding more independent variables to a model will only increase R2 if they provide meaningful variation. Adj R2 measures the proportion of the variation in the dependent variable that has been explained by the variation in the independent variable. If...
1. Suppose the true conditional mean function is but by mistake, a researcher ran least square regression without the X term as in Assume cou (Xi, U)-0, E Xil]-o and E [x?]-: i. Is his/her estimate consistent for β? If not, show which OLS assumption fails and discuss potential solutions. 2. Assume the structural equation is where E [111x,-0. It was discovered that we observe Xi with a measurement error wi instead of the real value Xi It is known...