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3. A response variable is related to a predictor variable through the quadratic regression model u...
Type or pas
2. Let the population regression model between a dependent variable y and an independent variable is given by y= Bo+ B1 x x+ u Suppose that E(u|x) = E(u) = 0 and V(ux) = o2. Based on a random sample ((y, ) i = 1,2,...n) of size n such that (xi- )2>0, let Bo and B be the OLS estimates of Bo and Bi respectively. Answer the following questions (c) Let B i Show that if B1...
The standard linear regression model is: y = Xw+e, where X is an nxd matrix of predictor vari- ables, y is an n-dimensional vector of response variables, and e N (0,021) is an n-dimensional vector of model errors. (a) What is the PDF of y in terms of X,w, o?? N(0,p1). (b) Let the PDF from part (a) be denoted as fylw). Suppose also in this case that w Write an expression for the joint PDF of w and y...
2. Consider a simple linear regression model for a response variable Yi, a single predictor variable ri, i-1,... , n, and having Gaussian (i.e. normally distributed) errors Ý,-BzitEj, Ejį.i.d. N(0, σ2) This model is often called "regression through the origin" since E(Yi) 0 if xi 0 (a) Write down the likelihood function for the parameters β and σ2 (b) Find the MLEs for β and σ2, explicitly showing that they are unique maximizers of the likelihood function. (Hint: The function...
Question 1 (4 points] 1. [1 point] Suppose the regression model is logarithmic: log(Y) = B1 + B2 log(X) +u. The estimate of B2 is 0.035. What is the interpretation of this coefficient? 2. (1 point] Suppose the regression model is semi-logarithmic: log(Y) = Bi + B2X + u. The estimate of B2 is 0.035. What is the interpretation of this coefficient? 3. [1 point] Suppose the regression model has quadratic term: Y = Bi+B2X + B3 X2 +u. The...
Q4. You analyze the non-linear relationships of two financial securities by fitting both a linear and a quadratic function with EXCEL linear model ret_A = a + b1 * ret_B + error Coefficients Standard Error of coefficients A 0.0000 0.0006 b1 -1.978 0.025 and Nonlinear model ret_A = a + b1 * ret_B + b2 * ret_B2 + error variable Coefficients Standard Error of coefficients a 0.0000 0.0006 b1 -1.850 0.0245 b2 4.45 0.382 Calculate the t-stat for the coefficient...
Problem 2: For logistic regression with 1 predictor variable, the model is specified as E(Y|X=x) 1-E(Y|X=x) Derive the formula to show th 1+e (Bo+B1x)
I figured the number 380.25 should related to quadratic model.
is it correct> if it is, how did he get this number tho. if not,
how did he get the number
Thanks
Problem For Exercise 12.8 on page 451, construct a 90%_cenidence inteaval for the mean compressive strength when the concentration is x = 19.5 and a adratic model used 12.8 The following is a set of coded experimental cata on the compressive strength of a particular alloy at var-...
Use the accompanying regression constants and coefficients to complete parts (a) through (e) below. A. Constant= 1.4. Coefficient b1= 0.8 Coefficient b2= -0.6 Coefficient b3= 9.73 B. Constant= 9.7 Coefficient b1= -0.6 Coefficient b2= 11.1 Coefficient b3= -8.96 C. Constant= 2.6 Coefficient b1= 0.2 Coefficient b2= 6.39 Coefficient b3= 3.42 D. Constant= 9.3 Coefficient b1= -0.8 Coefficient b2= 21.72 Coefficient b3= 1.38 (a) Determine the multiple linear prediction rule for predicting criterion variable Y from predictor variables Upper X 1,...
Question 1 (4 points) 1. [1 point) Suppose the regression model is logarithmic: log(Y) = B1 + Blog(X) + u. The estimate of B2 is 0.035. What is the interpretation of this coefficient? 2. 1 point Suppose the regression model is semi-logarithmic: log(Y) = 8 + B,X + u. The estimate of B2 is 0.035. What is the interpretation of this coefficient? 3. [1 point) Suppose the regression model has quadratic term: Y = B1+ B2X + B3X²+u. The estimate...
Computer output for fitting a simple linear model is given below.State the value of the sample slope for this model and give the null and alternative hypotheses for testing if the slope in the population is different from zero. Identify the p-value and use it (and a 5% significance level) to make a clear conclusion about the effectiveness of the model. The regression equation is Y - 78.8 -0.014. Predictor Coef SE Coef T P Constant 78.79 11.30 6.97 0.000...