1 For Part (I) you will develop an Excel template using the data in Table 1 and answer the accompanying questions (1) through (12). We will call this estimated equation (1) - Model REG1. 2 For Part (II), you will develop a multiple regression model template in Excel for two independent variables, and answer questions (1) - (9). We will call this estimated equation (2) - Model REG2 3 For Part(III), using the Excel Data Analysis program, you will estimate a multiple regression model with three independent variables, that will provide the most accurate estimation of an individual demand curve for your Product Y by meeting all of the 'goodness-of-fit' and 'accuracy measurements' criterion. Call this estimated model REG3, and if it requires a new estimated model, call the new model REG4. [or equation (3)] 4 From this estimated model you will calculate the following statistical values for your marketing information and policy decisions. Call these metrics your 'internal/controllable' policy instruments. a. The own-price elasticity of demand b. The cross-price elasticity of demand c. The advertising elasticity of demand. d. The coefficient of partial determination which measures the contribution of each explanatory variable to the estimated multiple regression model. 5 After you have completed Parts (I) to (III), you will need to download Canadian GDP data from Table 1 below into your Excel template, for the years 2017/Q3 - 2023/Q2 which gives n = 24 observations. Table 1 Canada Gross Domestic Expenditures Gross Domestic Expenditures Based, Canada, Quarterly (x1,000,000), Table 36-10-0104 Prices = Current: Seasonal Adjustment = Unadjusted 2017/Q3 - 2023/Q2 2019 Q1 5,234 2021 Q1 5.435 2023 Q1 6.408 Q2 5 ,513 Q2 4.900 Q2 6.893 2017 Q3 5.302 Q3 5,885 Q3 5.820 Q4 5,297 Q4 5,725 Q4 5.913 2018 Q1 4,998 2020 Q1 5,396 2022 01 5.729 Q2 5,244 Q2 5.718 Q2 6.038 Q3 5,591 Q3 6.016 Q3 6.501 Q4 5,573 Q4 5.983 Q4 6.664 6 You will now have to estimate a univariate forecasting model ( of your choice) for GDP )that provides