PRODUCTION AND OPERATIONS MANAGEMENT BUS3020 COURSE CONTENT WEEK THREE TOPIC: FORECASTING • Different Methods of Forecasting – Formal and Informal, • Qualitative and Quantitative Methods • Causal methods auto projection methods of forecasting. What is forecasting? Forecasting is the art and science of predicting future events. As a science it uses historical data and projects them into the future using mathematical models. As an art it uses intuition or judgment to predict the future
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Controlling Demand through Pricing: A report on the quantitative analysis of the ChocoMint bar Introduction ChocoMint is a bar of chocolate under ChocoHeaven, which is a distributor of organic chocolate. In recent years, the business of ChocoMint bar encountered some problems. Since the ChocoMint bar is manufactured overseas, the supply chain could be unreliable. Besides, as ChocoMint is stored at special storage locations in the UK, the storage capacity for this kind of product in the UK is
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Stats Questions II 1.The table below displays a week's worth of data on daily sales at the Crank It Louder Music Store. ??Over that time period, what was the mean daily level of sales? A. ?$3,489.79 ?B. $4,071.42 ?C. $1,643.23 D. $2,829.92 2. The table below displays a week's worth of data on daily sales at the Crank It Louder Music Store. ??Over that time period, what was the median daily level of sales? A. $1,643.23 B. ?$3,489.79 C. ?$3,130.46 D. ?$800.12 3. The histogram below
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CI’s for differences between means Multiple comparison methods: LSD, Tukey, Bonferroni, and Scheffe Diagnostics of model assumptions and remedial measures: three key assumptions on the error terms of ANOVA/ transformation methods Residual analysis Regression model corresponding to ANOVA model Review problems: These are the minimum knowledge to get ready for the exam. You should study thoroughly text book material and lecture notes to be well prepared for the exam. 1. Indicate
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|0.0019 | |R-squared |0.996366 | Mean dependent var |83.86000 | |Adjusted R-squared |0.994688 | S.D. dependent var |28.97771 | |S.E. of regression |2.111972 | Akaike
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3 Ways to Improve Your Targeted Marketing with Analytics Introduction Targeted marketing is a simple concept, but a key element in a marketing strategy. The goal is to identify the potential customers who are most likely to buy what you are selling. Once you have identified this target group of people, you can focus your marketing efforts in their direction. This process could substantially decrease marketing costs. In this tutorial, you will use data from a Portuguese banking institution whose
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การวิเคราะห์เส้นทาง (Path Analysis) ความหมายการวิเคราะห์เส้นทาง การวิเคราะห์เส้นทาง เป็นการวิเคราะห์สาเหตุ โดยนักวิจัยต้องการศึกษาสาเหตุ ของปรากฏการณ์ต่าง ๆว่ามาจากอิทธิพลของสิ่งใด กล่าวอีกนัยหนึ่งก็คือ นักวิจัยต้องการ ค้นหาว่าตัวแปรตามที่กำลังศึกษานั้น เกิดจากอิทธิพลของตัวแปรอิสระอะไรบ้าง และตัว แปรอิสระนั้นมีอิทธิพลต่อตัวแปรตามมากน้อยเพียงใด (สำเริง บุญเรืองรัตน์, หน้า 91) การอธิบายสาเหตุของปรากฏการณ์ นักวิจัยต้องอาศัยความรู้และทฤษฏีต่าง ๆ มา วิเคราะห์เพื่อตั้งสมมติฐานด้วยการสร้างแผนภาพ
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Contents Meet the Audit Team 3 Partner Summary 5 Introduction 6 Part 1.1 a) Advanced Analytics in Professional Standards 6 Part 1.1 b) Academic Research on Advanced Analytical 6 Part 1.3 Simple Trend-line Regression 7 Part 2.1 Specific Risk of Material Misstatement 11 Part 2.2 An Appropriate Audit Program 12 Appendix 15 References 16 List of Key Audlish terms 17 Partner Summary In order to better understand
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oil prices. The purpose of this paper is to determine whether oil revenues have an effect on taxation. Understanding the effect of oil revenues on taxation is very important in terms of real world application. The information obtained from the analysis between the two variables will enable large producing oil nations to determine the kind of fiscal policy to undertake. It will help nations in planning budgets accordingly, while also helping governments determine whether there needs to be a change
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different symbols for the Mall and nonMall Stores 2. Run a regression of Sales on number of customers 3. Run a regression of Sales on both variables. a. Interpret the coefficient on the Mall variable b. Is this coefficient significant? c. Is the regression in part 3 an improvement on the one in part 2? Look at the change in R2 and adjusted R2. d. Show what is really “going on” in the regression by deriving the equation for sales in mall stores and for sales
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