CASE STUDY Forecasting Attendance at SWU Football Games Forecasting Attendance at SWU Football Games Southwestern University (SWU)‚ a large state college in Stephenville‚ Texas‚ 30 miles southwest of the Dallas/Fort Worth metroplex‚ enrolls close to 20‚000 students. In a typical town–gown relationship‚ the school is a dominant force in the small city‚ with more students during fall and spring than permanent residents. A longtime football powerhouse‚ SWU is a member of the Big Eleven
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Southwestern University (SWU)‚ located 30 miles southwest of the Dallas/Fort Worth metroplex‚ has witnessed tremendous growth in its football program. With that growth‚ fueled by the hiring of legendary coach Bo Pitterno‚ has come more fame‚ the need for a bigger stadium‚ and more complaints about seating‚ parking‚ long lines‚ and concession stand prices. Southwestern Universitys president‚ Dr. Marty Starr‚ was not only concerned about the cost of expanding the existing stadium versus building a
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Southwestern University is experiencing a quickly expanding football program. As a result‚ attendance for home games is increasing and approaching capacity. It is in the best interest of SWU to forecast attendance to aid them in deciding when the best time to expand the present stadium‚ which now holds 54‚000. Data: The following data is from the past six seasons‚ 2002-2007. Game Year – Game – Opponent Attendance 2002-1 Baylor 34200 2002-2 Texas 39800 2002-3 LSU 38200 2002-4 Arkansas 26900 2002-5 USC
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Forecasting Problem POM Software: For this part of the problem I need to use the POM software: 1. Forecasting. 2. I should select Module->Forecasting->File->New->Least Squares and multiple regression 3. Use the module to solve the Case Study (Southwestern University). this case study‚ I am are required to build a forecasting model. Assume a linear regression forecasting model and build a model for each of the five games (five models in total) by using the forecasting module of the
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On the first day of class many students hear about their professors’ attendance policies as they go over the expectations for the semester. School Attendance Policies Most schools expect students to attend all of their classes. After all‚ what would be the point in enrolling students to get an education and then figuring they didn’t need to actually show up? Specific attendance policies can vary from one school to another or even from one class to another. <<<(example)>>> The Responsibility of Students
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KRISHNA ENGINEERING COLLEGE NOTICE Ref: MCA/ May/ 01 / 2010 Date: 3rd May2010 Schedule for internal viva of MCA VI semester Mentor Group Date Time Venue Ms. Shikha Saxena 7th May’10 10:00 a m Lab-11 Ms. Sunita Chand 10th May’10 10:00 a m Lab-11 Ms. Saloni 10th May’10 10:00 a m Lab-11 Ms. Shweta Bhatnagar 11th May’10 10:00 a m Lab-11 Prof. Vikas Chaudhary 12th May’10 10:00 a m Lab-11 Prof. Radhakrishnan 13th May’10 10:00 a m Lab-11
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Forecasting Cassandra Harris HSM/260 5/3/2015 Cynthia Cucuzza Forecasting Exercise 9.1 The following data represent total personnel expenses for the Palmdale Human Service Agency for past four fiscal years: 20 X 1 = $5‚250‚000 20 X 2 = $5‚500‚000 20 X 3 = $6‚000‚000 20 X 4 = $6‚750‚000 Forecast personnel expenses for fiscal year 20X5 using moving averages weighted moving averages‚ exponential smoothing‚ and time series regression. For moving averages and weighted moving averages‚ use only the data
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Forecasting BUS446: Production Control (CFM1316A) Monday‚ April 29‚ 2013 Forecasting In the business world today‚ companies use forecasting methods to implement processes and strategies in order to meet organizational goals. Forecasting will allow a company to plan for possible outcomes‚ making adjustments to inventory levels and staff. Through forecasting‚ companies will attempt to keep operating costs at a manageable level without sacrificing production and quality.
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Forecasting is the process of making statements about events whose actual outcomes (typically) have not yet been observed. A commonplace example might be estimation of some variable of interest at some specified future date. Prediction is a similar‚ but more general term. Both might refer to formal statistical methods employing time series‚ cross-sectional or longitudinal data‚ or alternatively to less formal judgemental methods. Usage can differ between areas of application: for example‚ in hydrology
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Demand Forecasting Importance Demand forecasts form the basis of all supply chain planning. Forecast of future demand are essential for making accurate supply chain decisions and ensuring the company’s success. Examples of such decisions include how much of the product to make‚ how much to inventory‚ how much to replenish and how much to order. Ease of Forecasting Beverages are a push product. Forecasting is not easy in the beverage industry as there are possible serious fluctuations in demand
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