Q1: Regression Analysis: (3 Marks) At PRIMO's Pizza, the operations manager was asked to establish a PRIMO'S pricing policy on their popular Sea Ranch Pizza. Experimenting with AMERICAN PIZZA Year prices produced the following data: Average Number of Sea Ranch Pizzas Sold Per Year across all branches Average Number of Sea Ranch Pizzas Sold Per Year across all branches Price in EGP Year Price in EGP 2014 20,000 100 2019 21,000 140 2015 19,000 105 2020 19,000 140 2016 18,800 105 2021 22,800 160 2017 18,000 120 2022 23,000 165 2018 17,000 135 2023 20,500 190 Required a. Plot the data and a regression line on the same graph. b. Determine the correlation coefficient and interpret it. c. Develop and interpret the regression line for the above-mentioned data series. d. In your own opinion, what other factors the operations manager at PRIMO's Pizza might think about regarding their impact on lobster's sales revenues. Q2: Forecasting Analysis: Assum that you got the following values of the number of units sold of Sea Ranch Pizza at PRIMO's during the previous ten years: You were asked to conduct a forecasting analysis to get the potential Sea Ranch Pizza's sales volumes during year 2024 using the following instructions: (7 Marks) Pizza's Sales in Year Units 2014 20,000 2015 19,000 2016 18,800 2017 18,000 2018 17,000 2019 21,000 2020 19,000 2021 22,800 2022 23,000 2023 20,500 2024 ?? (c) (a) Under what circumstances should PRIMO's use qualitative forecasting? (b) Why do time-series forecasting methods work well for short-term forecasting but do not work very well in long-term forecasting? Use Nave approach. (1 mark) (1 mark) (0.5 mark) (d) Depend on a 6-year moving average approach to get an averaged- forecasted Value. (0.5 mark) (e) Use the following weights to get a weighted forecasted value. (0.07, 0.08, 0.15, 0.18, 0.22, 0.30), Interpret your distributions of weight with different years. (0.5 mark) (f) (g) Use exponential smoothing approach (use a = 0.40 in your analysis). Compute MAD and MSE to compare which one seems the most appropriate and accurate approach of the previous four approaches & why? (1.5 marks) (1 mark) (h) What is the need to have multiple measures of forecast errors -MAD and MSE? (1 mark)