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[1]:
[1] Round numbers to four decimal points (e.g. 0.1234), unless explicitly requested otherwise.
Group No. : Group Members: 361 Course Project—Part Three 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[footnoteRef:1]: [1: Round numbers to four decimal points (e.g. 0.1234), unless explicitly requested otherwise.] 1. To provide a bar chart (with data labels rounded to two decimal points) showing the average demand for each week day (Sun., Mon., etc.) 2. To fit a simple linear regression model to the data and to provide its equation (d = a*t + b), along with R2 d = R2= 0.93 3. To fit a multiple regression model with a dummy variable representing the weekend, and to provide the regression equation (d = a*t + b*w + c), along with R2. d = Adjusted R2= 4. To provide a run-series plot of the actual demand with simple regression and multiple regression overlay. [add chart here] 5. To write a short paragraph explaining the observations and providing general recommendations for the next seven days demand forecast. [write your paragraph here] 6. To fit a new multiple regression model with dummy variables for seven days in a week (Mon, Tue, …, Sun), and to provide the regression equation (d = a*t + b1x1 + b2x2 + b3x3 + b4x4 + b5x5 + b6x6 + c), along with R2. d = R2= 7. To use all three models: · M1: d = 1.0356t + 339.29 · M2: d = 0.7163t + 116.7679w + 315.0262 · M3: (the one considering weekdays) to predict the demand for seven days ahead (Mon, Tue, …, Sun) and find the total weekly demand. M1 M2 M3 Mon. Tue. Wed. Thu. Fri. Sat. Sun. TOTAL: 8. Take advantage of the fact that new demand data became available and use this new data to compare the forecasts using MAPE for days 57-63. New: M: 311 T: 341 W: 357 Th: 363 F: 390 Sa: 490 Su: 492 MAPEM1: MAPEM2: MAPEM3: 9. To provide a line chart with the actual demand (including the new data) and M2 and M3. 10. To choose the best model for forecasting daily demand at Orchid Relief for 7 days ahead and write a short paragraph explaining your choice. [write your paragraph here] Average demand on week days Average demand MonTuesWedThuFri301.375315.12499999999994342.75334380.37500000000006Week days Average demand 1