values, 1/2 and 1: Pr(0-1)= a and Pr(0= qual to s. Suppose that the search engine induces expected relevance 0. Show th is v² = 1- 28 8€ What is the price charged by a firm of quality and its profit? Express search engine's fee and profit in terms of 0*, 0 and s. Suppose that a = 1/8. What is search engine's profit if it induces high if its profit when it induces distorts search, i.e. 0 = 1/2? Which fee sh
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- Determine the mean waiting time W for an M/M/2 system when lambda = 2 and μ = 1.2. Compare this with the mean waiting time in an M/M/1 system whose arrival rate is lambda = 1 and service rate is μ = 1.2. Since the arrival rate per server is the same in both cases and service times don’t vary, should the wait times be the same in both cases?In a continuous-time surplus model, the claim severity is distributed as BN(2, 0.4). Determine the Lundberg upper bound for the probability of ultimate ruin if the initial surplus is 2 and the prIn a continuous-time surplus model, the claim severity is distributed as BN(2, 0.4). Determine the Lundberg upper bound for the probability of ultimate ruin if the initial surplus is 2 and the premium loading factor is 0.25.emium loading factor is 0.25.Design a 3rd order Least-squares function approximation to interpolate between the mid between (2n and 3") for a dataset as chosen by you. Compute the LS model error.
- Find the minimum mean square error forecast Y(1), forecast error e, (1) and Varfe, (1)1 for the following modes. Y, = 0.8Y, +e,. Y, = 3+21+e,.The number of clients a store has during a week is Poisson distributed with - 25. The amount of money spent by each client follows a random = el,000t+250t2. Assuming the mean A variable with moment generating function o(t) independence between the number of clients, and the amount of money spent by each client. Find the mean and variance of the amount of money received by the store every week.In the least-squares line = 5 + 2x, what is the marginal change in for each unit change in x?
- Consider the following population model for household consumption: cons = a + b1 * inc+ b2 * educ+ b3 * hhsize + u where cons is consumption, inc is income, educ is the education level of household head, hhsize is the size of a household. Suppose a researcher estimates the model and gets the predicted value, cons_hat, and then runs a regression of cons_hat on educ, inc, and hhsize. Which of the following choice is correct and please explain why. A) be certain that R^2 = 1 B) be certain that R^2 = 0 C) be certain that R^2 is less than 1 but greater than 0. D) not be certainUse least squares regression to fit polynomials of order 1, 3 and 5 to the data given in table. Compute the correlation coefficient for each fit (Use Gauss elimination with partial pivoting in the solution of linear equation systems). Plot 1st, 3rd, and 5th order polynomial fits and the given discrete data. Comment on which of these curves explain better the variability of given data. I have a solution at second image but i dont understand where did the functions like "y=2.3021x^3+..." come from? I need a detailed description about it. Thank youA regression and correlation analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x). Σx = 90 Σ(y - )(x - ) = 466 Σy = 170 Σ(x - )2 = 234 n = 10 Σ(y - )2 = 1434 SSE = 505.98 The least squares estimate of the slope or b1 equals a. .923. b. 1.991. c. -1.991. d. -.923.
- The least squares regression line for a set of data is calculated to be y = 24.8 + 3.41x. (a) One of the points in the data set is (4, 37). Calculate the predicted value. (b) For the point in part (a), calculate the residual.Find the least-squares regression line ŷ = ba + b₁ through the points (−2, 2), (3, 6), (5, 14), (8, 19), (10, 27), and then use it to find point estimates corresponding to x = 1 and x = = 7. For x = 1, y = For x = 7, y =bx Find the curve of best fit of the type y = ae^ to the following data by the method of Least Squares. X y 1 10 5 15 7 12 9 15 12 21