If {xt } is stationary with E [xt] = 0 and corr(xt , xt −1) = rho1, show that the best linear predictor of xt based on xt −1 is rho1xt −1. (You will need to use calculus to do this problem. Here are some hints. First, define the random variables Y = xt , X = xt −1. Consider any linear predictor Yˆ = a + bX , where a and b are any numbers. Consider the mean squared forecasting error, MSE = E [Y − Yˆ] 2 = E [Y − (a + bX )]2.

Pleasse me i need an answer. give me the correct answer. answer if you know it ! the club will base its decision about whether to increase the budget for the indoor rock climbing facility on the analysis of its usage. the decision to increase the budget will depend on whether members are using the indoor facility at least two times a week. use the best measure of center for both data sets to determine whether the club should increase the budget. assume there are four weeks in a month. if you think the data is inconclusive, explain why.