Question
Project Case description: Forecasting Food and Beverage Sales The Vintage Restaurant, on Captiva Island near Fort Myers, Florida, is owned and operated by Karan
Project Case description: Forecasting Food and Beverage Sales The Vintage Restaurant, on Captiva Island near Fort Myers, Florida, is owned and operated by Karan Payne. The restaurant just completed its third year of operation. During those three years, Karen sought to establish a reputation for the restaurant as a high-quality dining establishment that specializes in fresh seafood. Through the efforts of Karen and her staff, her restaurant has become one of the best and fastest-growing restaurants on the Island. To better plan for future growth of the restaurant, Karen needs to develop a system that will enable her to forecast food and beverage sales by month for up to one year in advance. The Excell file Vintage.xlsx has the data. It shows the value of food and beverage sales ($1,000s) for the first three years of operation (Observations #1 -12: Year 1; Observation #13 - 24: Year 2; Observations #25-36: Year 3). Analysis: Perform an analysis of the sales data for the Vintage Restaurant. Prepare a report for Karen that summarizes your findings, forecasts, and recommendations. Include the following: 1. A time series plot. Comment on the underlying pattern in the time series. 2. Using the dummy variable approach, forecast sales for January through December of the fourth year. For this, follow the steps below: a. First, create 11 dummy variables to represent the months January - November. Then use these variables in the regression model only with seasonal effects. b. Next, fit another regression model with both linear trend and seasonal effects. c. Compare these two models with respect to the forecast errors. You can use the "forecast accuracy template" posted on the website for these calculations. d. Based on the "best" model, generate the forecasts mentioned above. e. How would you explain these models and results to Karen? 3. Assume that January sales for the fourth year turn out to be $295,000. What was your forecast error? If this error is large, Karen may be puzzled about the difference between your forecast and the actual sales value. What can you do to resolve her uncertainty about the forecasting procedure? Report Preparation: Please complete the following tasks for the report: a) Describe the problem background and purpose of the study b) Describe the data and variables included in the case c) Outline the statistical method required to answer the research questions d) Apply the models to answer the questions above sequentially a. Follow all steps required to conduct a complete analysis and validation of methods as outlined above e) Present the results nicely and interpret those 1) Final conclusions, decision-making and recommendations based on the results to Karen Important note: Please follow the grading rubric and the report preparation guidelines carefully while preparing the final report. Remember to focus on the writing as well-grammar, typos, flow and organization are key components. Data Sheet2 Sheet3 Month Sales 1 242 2 235 3 232 4 178 5 184 161 6 140 7 145 8 00 152 9 110. 10 130 11 152 12 206 13 263 14 238 15 247 16 193 17 193 18 149 19 157 20 161 21 122 22 130 23 167 24 230 25 282 26 255 27 265 28 205 29 210 30 160 31 166 23233 174 126 34 148 35 173 36 235 Please review this while preparing your project report. Section Points Introduction and background 2 Questions of interest, variable 5 descriptions, data exploration Forecasting model, evaluation, other 5 issues Presentation and interpretation of results Final conclusions Overall quality & flow* Total 5 2 20
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