1, (3%) Provide the appropriate definitions of 1.1 Business forecasting (BF) 1.2 Predictive analytics (PA) 1.3 A structural forecasting model 1.4 A non-structural forecasting model 1.5 The autocorrelation function (acf) 2. (4%) Identify some similarities and differences between BF and PA. 3. (396) BF and PA are subjet to criticisms. What are they? 4. (4%) 4.1 How to use the act to determine whether a time-series data set is stationary, nonstationary, seasonal, and/or random? 4.2 How to transform a nonstationary time-series data set into a stationary one? (6%) Suppose that you want to forecast Yi with three independent variables in the setting of a multiple linear structural model. The fitted forecasting model based on a cross-sectional data set of 15 observations is given as follows: 5, F-5638+2385X +1859x3455X3i (-4.27) (1.69) (0.79) (1.33) s 1849, R2-0.838, 0.790,Az-0.600,h3 0.643, and 3-: 0.930. 5.1 Do you think the fitted forecasting model is acceptable? Why? Discuss. 5.2 What is the major problem? Explain. 5.3 Recommend one way to improve the forecasting model