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3. Suppose the following data has been obtained for the linear model Y -Bo+ yi 4 02-2 (a) Find th...
3. Suppose the following data has been obtained for the linear model Y Bo+ x 14 2 1 4 0 22 (a) Fi...
a,b,c,d
3. Suppose the following data has been obtained for the linear model Y Bo+ x 14 2 1 4 0 22 (a) Find the OLS estimators βο and A using the non-matrix method. (b) Find the OLS estimators using the matrix method. (c) Find the coefficient of determination. (d) Find the standard error of
3. Suppose the following data has been obtained for the linear model Y Bo+ x 14 2 1 4 0 22 (a) Find the OLS...
Consider the linear model: Yi = α0 + α1(Xi − X̄) + ui. Find the OLS...
Consider the linear model: Yi = α0 + α1(Xi − X̄) + ui.
Find the OLS estimators of α0 and α1. Compare with the OLS
estimators of β0 and β1 in the standard model discussed in class
(Yi = β0 + β1Xi + ui).
Consider the linear model: Yį = ao + Q1(X; - X) + Ui. Find the OLS estimators of do and a1. Compare with the OLS estimators of Bo and B1 in the standard model discussed in...
3. Consider simple linear regression model yi = Bo + B12; + &; and B. parameter...
3. Consider simple linear regression model yi = Bo + B12; + &; and B. parameter estimate of the slope coefficient Bi: Find the expectation and variance of 31. Is parameter estimate B1 a) unbiased? b) linear on y? c) effective optimal in terms of variance)? What will be your answers if you know that there is no intercept coefficient in your model?
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....
Problem 3: Assume that 'nature' behaves according to the following linear additive model: Y = Bo...
Problem 3: Assume that 'nature' behaves according to the following linear additive model: Y = Bo + B1X +€, where ε is a Gaussian random variable N (0,02). Using this model, nature generates the following training dataset: D = {(Li, yi)}}–1 = {(–2, 47/2),(-1, -3), (0,0), (1,3), (2,7/2)}. Please, answer the questions below without the help of any computer software: a. Compute the estimates of Bo and @1 for a linear estimator û = Bo + 1X using the data...
1. Suppose you are interested in estimating the following model: Yi = Bo + B11; +u;...
1. Suppose you are interested in estimating the following model: Yi = Bo + B11; +u; where B, is the coefficient of interest in the model. Unfortunately, you have reason to believe that couci, u) +0. Suppose you also have data on another variable, zi, and its relationship to I, is as follows: Di = 0o + Q121 + Ei (b) Using Method of Moments, derive IV. Be sure to show all steps and clearly state the logic behind each.
Consider the following regression model: Xi = Bo + Bixi + y; where yi is individual...
Consider the following regression model: Xi = Bo + Bixi + y; where yi is individual i's University GPA and xi is the individual's high school grades. a. What do you think is in ui? Do you think E[ulx) = 0? Suggest a variable that you think might affect University GPA that isn't included in the regression equation but should be. c. What sign of bias would you expect in an OLS regression of y on x? Briefly explain. d....
2. Suppose Y ~ Exp(a), which has pdf f(y)-1 exp(-y/a). (a) Use the following R code to generate data from the model Yi...
2. Suppose Y ~ Exp(a), which has pdf f(y)-1 exp(-y/a). (a) Use the following R code to generate data from the model Yi ~ Exp(0.05/Xi), and provide the scatterplot of Y against X set.seed(123) n <- 500 <-rnorm (n, x 3, 1) Y <- rexp(n, X) (b) Fit the model Yi-Ao + Ax, + ε¡ using the lm function in R and provide a plot of the best fit line on the scatterplot of Y vs X, and the residual...
Find the sample variance of the dependent variable yi. What fraction of the sample variance in...
Find the sample variance of the dependent variable
yi.
What fraction of the sample variance in
yi can be explained by the linear regression
model? Find the coefficient of determination,
r2.
Find the adjusted r2
value.
Do we have enough evidence to conclude that there exists
a strong linear relationship between xi and
yi? Find the p-value for the
test.
Problem. Chris Pratt is almost ready to pop the question to the girl of his dreams. He collected the data...
Suppose that the data (X1, Y), ... (Xn, Yn is generated by the following ("true") model: a+ bX; + сX; +ei, wher...
Suppose that the data (X1, Y), ... (Xn, Yn is generated by the following ("true") model: a+ bX; + сX; +ei, where a, b, c are some parameters and ei are independent errors with zero mean and variance a2. Suppose that we fit the simple linear regression model to the data (i.e. we ignore the quadratic term cX2) using the OLS method. Find the expectation of the residual from the fit.
Suppose that the data (X1, Y), ... (Xn, Yn...
a,b,c,d
3. Suppose the following data has been obtained for the linear model Y Bo+ x 14 2 1 4 0 22 (a) Find the OLS estimators βο and A using the non-matrix method. (b) Find the OLS estimators using the matrix method. (c) Find the coefficient of determination. (d) Find the standard error of
3. Suppose the following data has been obtained for the linear model Y Bo+ x 14 2 1 4 0 22 (a) Find the OLS...
Consider the linear model: Yi = α0 + α1(Xi − X̄) + ui.
Find the OLS estimators of α0 and α1. Compare with the OLS
estimators of β0 and β1 in the standard model discussed in class
(Yi = β0 + β1Xi + ui).
Consider the linear model: Yį = ao + Q1(X; - X) + Ui. Find the OLS estimators of do and a1. Compare with the OLS estimators of Bo and B1 in the standard model discussed in...
3. Consider simple linear regression model yi = Bo + B12; + &; and B. parameter estimate of the slope coefficient Bi: Find the expectation and variance of 31. Is parameter estimate B1 a) unbiased? b) linear on y? c) effective optimal in terms of variance)? What will be your answers if you know that there is no intercept coefficient in your model?
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....
Problem 3: Assume that 'nature' behaves according to the following linear additive model: Y = Bo + B1X +€, where ε is a Gaussian random variable N (0,02). Using this model, nature generates the following training dataset: D = {(Li, yi)}}–1 = {(–2, 47/2),(-1, -3), (0,0), (1,3), (2,7/2)}. Please, answer the questions below without the help of any computer software: a. Compute the estimates of Bo and @1 for a linear estimator û = Bo + 1X using the data...
1. Suppose you are interested in estimating the following model: Yi = Bo + B11; +u; where B, is the coefficient of interest in the model. Unfortunately, you have reason to believe that couci, u) +0. Suppose you also have data on another variable, zi, and its relationship to I, is as follows: Di = 0o + Q121 + Ei (b) Using Method of Moments, derive IV. Be sure to show all steps and clearly state the logic behind each.
Consider the following regression model: Xi = Bo + Bixi + y; where yi is individual i's University GPA and xi is the individual's high school grades. a. What do you think is in ui? Do you think E[ulx) = 0? Suggest a variable that you think might affect University GPA that isn't included in the regression equation but should be. c. What sign of bias would you expect in an OLS regression of y on x? Briefly explain. d....
2. Suppose Y ~ Exp(a), which has pdf f(y)-1 exp(-y/a). (a) Use the following R code to generate data from the model Yi ~ Exp(0.05/Xi), and provide the scatterplot of Y against X set.seed(123) n <- 500 <-rnorm (n, x 3, 1) Y <- rexp(n, X) (b) Fit the model Yi-Ao + Ax, + ε¡ using the lm function in R and provide a plot of the best fit line on the scatterplot of Y vs X, and the residual...
Find the sample variance of the dependent variable
yi.
What fraction of the sample variance in
yi can be explained by the linear regression
model? Find the coefficient of determination,
r2.
Find the adjusted r2
value.
Do we have enough evidence to conclude that there exists
a strong linear relationship between xi and
yi? Find the p-value for the
test.
Problem. Chris Pratt is almost ready to pop the question to the girl of his dreams. He collected the data...
Suppose that the data (X1, Y), ... (Xn, Yn is generated by the following ("true") model: a+ bX; + сX; +ei, where a, b, c are some parameters and ei are independent errors with zero mean and variance a2. Suppose that we fit the simple linear regression model to the data (i.e. we ignore the quadratic term cX2) using the OLS method. Find the expectation of the residual from the fit.
Suppose that the data (X1, Y), ... (Xn, Yn...
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