Mini Case 1 Eli Orchid has designed a new pharmaceutical product, Orchid Relief, which improves the night sleep. Before initiating mass production of the product, Eli Orchid has been market-testing Orchid Relief in Orange County over the past 8 weeks. The daily demand values are recorded in the Excel file provided. Eli Orchid plans on using the sales data to predict sales for the upcoming week. An accurate forecast would be helpful in making arrangements for the company's production processes and designing promotions. Before a forecasting model is built and a forecast for the next week is generated, the COO of the company has asked the data analyst for an exploratory analysis of the demand. Specifically, the COO has asked the analyst: To provide a bar chart (with data labels rounded to two decimal points) showing the average demand for each week day (Sun., Mon., etc.) Weekday Sun Sat Fri Thu Average Demand per Weekday 453.25 454.75 380.38 334.00 Wed 342.75 Tue Mon 315.13 301.38 0.00 100.00 200.00 300.00 400.00 Average Demand 500.00 To fit a simple linear regression model to the data and to provide its equation (d = a*t + b), along with R d = R- To fit a multiple regression model with d= a dummy variable representing the weekend, and to provide the regression equation (d = a*t + b*w+ c), along with Adjusted R. To provide a run-series plot of the actual demand with simple regression and multiple regression overlay. Adjusted R= [add chart here]