Learning Reinforcement Activity No. 6-1: FORECASTING MODELS Accomplish by November 7, 2020 Use Microsoft Excel to solve the following problems on forecasting models. Use one worksheet per model. Save your Excel outputs as an xlsx file. Your answers, equations, conclusions and other discussions must be placed in a .docx file following a similar flow/format as presented in this module. You may also submit a .pdf file for verification purposes. Use four decimal places for regression coefficients and other computed values. The consumption of Electrical and Electronic Equipment (EEE) is strongly linked to widespread global economic development. It has become indispensable in modem societies and is enhancing living standards. Higher levels of disposable incomes, growing urbanization and mobility, and further industrialization in some parts of the world are leading to growing amounts of EEE. After its use. EEE is disposed of generating a waste stream that contains hazardous and valuable materials. This waste stream is referred to as e-waste. In 2019. the world generated a striking 53.6 metric tons of e-waste, an average of 7.3 kg per capito (per person). The table below shows the per capita electronic waste generation worldwide from 2010 to 2019. in kilograms per capita. 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Year Volume of waste (in kg per capita) 5.0 5.2 5.4 5.7 6.4 6.6 6.8 6.9 2.1 7.3 1. Forecast the volume of waste generated in 2020 using a 3-year, 5-year, and 7-year average. (5 points) 2. Using a smoothing coefficient of 0.6, exponentially smooth the series and forecast the volume of waste generated in 2020. (10 points) 3. Compute a linear trend forecasting equation and forecast the volume of waste generated in 2020 2021 and 2022. (10 points) 4. Compute a quadratic trend forecasting equation and forecast the volume of waste generated in 2020, 2021. and 2022. (10 points)