Homework Answers
(2) Let be a linear function of X, ie. = bo +b1X where bo and bi...
(2) Let be a linear function of X, ie. = bo +b1X where bo and bi are fixed real numbers. We want to minimize the discrepancy of Y from Y, i.e. minimizing the quantity a) Find the values of bo and bi that minimizes Q (b) Use (a) to show that the minimal value of Q is σ -c 3xy 2 Cov2 (X.y Hint: You may use the fat that (b,bE[(Y -Yar (Y - Y)E(Y - Y) where Y.-bg +...
Let Y be a linear function of X, i.e. Y = bo + bịX where bo...
Let Y be a linear function of X, i.e. Y = bo + bịX where bo and bl are fixed real numbers. We want to minimize the discrepancy of Y from Y, i.e. minimizing the quantity (a) Find the values of bo and bi that minimizes Q (b) Use(a) to show that the minimal value of Q is Co - Hint: You may use the fact that Q(bg, b) [(Y-Y*)2] = Var (Y-Y*) +E(Y-Y*)]2 where Y*-bg + bİX and bi,...
I am having trouble with part b. Please explain. (2) Let Y be a linear function...
I am having trouble with part b.
Please explain.
(2) Let Y be a linear function of X, ie. Y lo +biX where bo and bi are fixed real numbers. We want to minimize the discrepancy of Y from Y, i.e. minimizing the quantity (a) Find the valucs of bo and bi that minimizes Q (b) Use (a) to show that the minimal value of Q is 2 Cov2(x,y) Hint: You may use the fact that Q(bg, bị) E [(Y-Y*)2-Var...
1. Let X and Y b e random variables, with μΧ = E(X), μΥ = E(Y),...
1. Let X and Y b e random variables, with μΧ = E(X), μΥ = E(Y), σ炙= Var(X) and σ Var(Y) (2) Let Ỹ be a linear function of X, ie. Ỹ = +51X where bo and bl are fixed real numbers. We want to minimize the discrepancy of Y from Y, i.e. minimizing the quantity (a) Find the values of bo and bi that minimizes Q (b) Use (a) to show that the minimal value of Q is σ....
(8 points) Consider the linear equation y = bo +bix. a. In the equation, bo is...
(8 points) Consider the linear equation y = bo +bix. a. In the equation, bo is A. the dependent variable B. the slope C. the y-intercept D. the independent variable b. In the equation, b, is A. the independent variable B. the slope C. the y-intercept D. the dependent variable C. Give the geometric interpretation of bo. It indicates A. how much the x-value on the straight line changes when the y-value increases by unit B. the x-value where the...
Suppose we fit the simple linear regression model (with the usual assumptions) Y = Bo+B1X+ €...
Suppose we fit the simple linear regression model (with the usual assumptions) Y = Bo+B1X+ € and get the estimated regression model ♡ = bo+bix What aspect or characteristic of the distribution of Y does o estimate? the value of Y for a given value of X the total variability in Y that is explained by X the population mean number of Y values above the mean of Y when X = 0 the increase in the mean of Y...
1. Consider the simple linear regression model: Ү, — Во + B а; + Ei, where 1, . . , En are i.i.d. N(0,02), for i1,2,......
1. Consider the simple linear regression model: Ү, — Во + B а; + Ei, where 1, . . , En are i.i.d. N(0,02), for i1,2,... ,n. Let b1 = s^y/8r and bo = Y - b1 t be the least squared estimators of B1 and Bo, respectively. We showed in class, that N(B; 02/) Y~N(BoB1 T;o2/n) and bi ~ are uncorrelated, i.e. o{Y;b} We also showed in class that bi and Y 0. = (a) Show that bo is...
6. This problem considers the simple linear regression model, that is, a model with a single...
6. This problem considers the simple linear regression model, that is, a model with a single covariate r that has a linear relationship with a response y. This simple linear regression model is y = Bo + Bix +, where Bo and Bi are unknown constants, and a random error has normal distribution with mean 0 and unknown variance o' The covariate a is often controlled by data analyst and measured with negligible error, while y is a random variable....
2. Consider the simple linear regression model: where e1, .. . , es, are i.i.d. N (0, o2), for i= 1,2,... , n. Suppose...
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...
Problem 1: Consider the model Y = BO + Bi X+e, where e is a N(0,02)...
Problem 1: Consider the model Y = BO + Bi X+e, where e is a N(0,02) random variable independent of X. Let also Y = Bo + B1X. Show that E[(Y - EY)^3 = E[(Ỹ – EY)^3 + E[(Y – Y)1.
(2) Let be a linear function of X, ie. = bo +b1X where bo and bi are fixed real numbers. We want to minimize the discrepancy of Y from Y, i.e. minimizing the quantity a) Find the values of bo and bi that minimizes Q (b) Use (a) to show that the minimal value of Q is σ -c 3xy 2 Cov2 (X.y Hint: You may use the fat that (b,bE[(Y -Yar (Y - Y)E(Y - Y) where Y.-bg +...
Let Y be a linear function of X, i.e. Y = bo + bịX where bo and bl are fixed real numbers. We want to minimize the discrepancy of Y from Y, i.e. minimizing the quantity (a) Find the values of bo and bi that minimizes Q (b) Use(a) to show that the minimal value of Q is Co - Hint: You may use the fact that Q(bg, b) [(Y-Y*)2] = Var (Y-Y*) +E(Y-Y*)]2 where Y*-bg + bİX and bi,...
I am having trouble with part b.
Please explain.
(2) Let Y be a linear function of X, ie. Y lo +biX where bo and bi are fixed real numbers. We want to minimize the discrepancy of Y from Y, i.e. minimizing the quantity (a) Find the valucs of bo and bi that minimizes Q (b) Use (a) to show that the minimal value of Q is 2 Cov2(x,y) Hint: You may use the fact that Q(bg, bị) E [(Y-Y*)2-Var...
1. Let X and Y b e random variables, with μΧ = E(X), μΥ = E(Y), σ炙= Var(X) and σ Var(Y) (2) Let Ỹ be a linear function of X, ie. Ỹ = +51X where bo and bl are fixed real numbers. We want to minimize the discrepancy of Y from Y, i.e. minimizing the quantity (a) Find the values of bo and bi that minimizes Q (b) Use (a) to show that the minimal value of Q is σ....
(8 points) Consider the linear equation y = bo +bix. a. In the equation, bo is A. the dependent variable B. the slope C. the y-intercept D. the independent variable b. In the equation, b, is A. the independent variable B. the slope C. the y-intercept D. the dependent variable C. Give the geometric interpretation of bo. It indicates A. how much the x-value on the straight line changes when the y-value increases by unit B. the x-value where the...
Suppose we fit the simple linear regression model (with the usual assumptions) Y = Bo+B1X+ € and get the estimated regression model ♡ = bo+bix What aspect or characteristic of the distribution of Y does o estimate? the value of Y for a given value of X the total variability in Y that is explained by X the population mean number of Y values above the mean of Y when X = 0 the increase in the mean of Y...
1. Consider the simple linear regression model: Ү, — Во + B а; + Ei, where 1, . . , En are i.i.d. N(0,02), for i1,2,... ,n. Let b1 = s^y/8r and bo = Y - b1 t be the least squared estimators of B1 and Bo, respectively. We showed in class, that N(B; 02/) Y~N(BoB1 T;o2/n) and bi ~ are uncorrelated, i.e. o{Y;b} We also showed in class that bi and Y 0. = (a) Show that bo is...
6. This problem considers the simple linear regression model, that is, a model with a single covariate r that has a linear relationship with a response y. This simple linear regression model is y = Bo + Bix +, where Bo and Bi are unknown constants, and a random error has normal distribution with mean 0 and unknown variance o' The covariate a is often controlled by data analyst and measured with negligible error, while y is a random variable....
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...
Problem 1: Consider the model Y = BO + Bi X+e, where e is a N(0,02) random variable independent of X. Let also Y = Bo + B1X. Show that E[(Y - EY)^3 = E[(Ỹ – EY)^3 + E[(Y – Y)1.
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