Question 5. Given sample data (x, y), and sample size n. We fit the simple regression model: and estimate the least square estimators (a) Suppose A,-1, ß,-2, and x-1. Compute у. b) Suppose S and sry...
2. Suppose we observe the pairs (X, Y), i-1, , n and fit the simple linear regression (SLR) model Consider the test H0 : β,-0 vs. Ha : Aメ0. (a) What is the full model? Write the appropriate matrices Y and X. (b) What is the full model SSE? (c) What is the reduced model? Write the appropriate matrix XR. (d) What is the reduced model SSE? (e) Simplify the F statistics of the ANOVA test of Ho B10 vs....
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...
Use least-square regression to fit the data with the following model y-a+bx+ x 6 9 15 16 y 10 15 2030 xjx2 x2 *1 Use least-square regression to fit the data with the following model y-a+bx+ x 6 9 15 16 y 10 15 2030 xjx2 x2 *1
2. Suppose we have the simple regression model Y =a+8X:+E, and their OLS coefficient estimators a and b. Answer the following questions. (a) Suppose we multiply X, by 1/2 for all i and do the OLS estimation again using X as the regressor (the independent variable). What will be your new estimators, denoted by ă (intercept) and b (slope)? Compare them with the original OLS estimators a and b, respectively (b) Compare Var[b] and Var[b]. Are they the same or...
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...
Probability and Statistics 1. Linear Regression Given 4 data points: X Y 5 15 Use simple linear regression to estimate ßo and ß, for the best-fit line ỹ ß0 + ßqx Calculate these values: x | 7 | S | Spy | Bo | Big Sketch the regression line and the data points below
Given a simple linear regression model with a sample size of n = 2; The sample data: (y1, x1), (y2, x2) (a) State the two normal equations in terms of the sample data (b) If there is only one observation (y1, x1) in the sample, how would the two normal equations look like? (c) What conclusion can we draw from the answer in part (a) and (b)?
Q6). Suppose that you want to fit two separate regression lines on the same data set - For the first least square fit, Y is the response variable and X is the predictor variable For the second least square fit, X is the response variable and Y is the predictor variable. (a). Show that the product of the slope estimates from the two regression lines is Show that the above two regression lines will never be perpendicular to each other...
Question 2: Suppose that we wish to fit a regression model for which the true regression line passes through the origin (0,0). The appropriate model is Y = Bx + €. Assume that we have n pairs of data (x1.yı) ... (Xn,yn). a) From first principle, derive the least square estimate of B. (write the loss function then take first derivative W.r.t coefficient etc) b) Assume that e is normally distributed what is the distribution of Y? Explain your answer...
2. Suppose we are given data on n observations (x,Y), i 1,... , n, and we have a linear model, = SXY/SXX and A,-ㄚ-Ax be the least-square estimates so that E(X) = β0 +ATp Let given in lecture. (a) Show that E(5xx)-A5xx and E(Y)-Ao +A2. (b) Use (a) to show that E(A)-A and E(A)-A. În other words, these are unbiased estimators (c) The fitted values Yi = ArtAz; are used as estimates of E(K), and the residuals ei = Y-...