Multiple regression models

Consider the following time series data. alllast getsa andi sbivorg t 102 823 0/ 4 09 5 -251752 bobramoos 9wow of for 9 14 15 Construct a time series plot. What type of pattern exists in the data? Develop the linear trend equation for this time series. . What is the forecast for t = 6? Consider the following time series data. + In O a. Construct a time series plot. What type of pattern exists in the data? b. Develop the linear trend equation for this time series. c. What is the forecast for t = 8? Consider the following time series. of 1 2 3 4 5 6 7 Y 120 110 100 96 94 92D Question 1 0.5 pts is a type of generalized linear model (GLM) that focuses on binary {or indicator) response variables, because regular linear regression is not well-suited to this kind of response variable. 0 Multiple regression O Logistic regression D Question 2 0.5 pts extends simple twovariable linear regression to cases where there are more than predictor (denoted 31, 3:2, 51:3, etc). 0 Multiple regression O Logistic regression Exercise 2 A. The least squares estimates for the coefcients in the straight line equation y = Bu + 31x are given by $105: f) (Pt J7) E?=1(xi - 332 Show that if)? = D and 37 = D, then bl] = F _ b1? and. bl = bl] = 0 And the expression for 3:11 simplifies to b = 231 350': 1 213:1"? B. Show that if j? = 0 and y = D, then 2:21 11% 1"\": n 2_ n 2 .' 5:137: .' =1yi where rm; is the sample correlation between X and Y. C. Use the expressions in A. and B. to show that $11.11*? 51 = er 7'7 1! Z [=1xi. (Hint: use that 2};le = J L1 x1? ' L1 xf)