Course Description This course applies quantitative reasoning skills to business problems. Students learn to analyze data using a variety of analytical tools and techniques. Other topics include formulas‚ visual representation of quantities‚ time value of money‚ and measures of uncertainty. Policies Faculty and students/learners will be held responsible for understanding and adhering to all policies contained within the following two documents: • University policies: You must be
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be able to: • • • • • • • understand the complexity of today’s managerial decisions know the meaning of quantitative techniques know the need of using quantitative approach to managerial decisions appreciate the role of statistical methods in data analysis know the various models frequently used in operations research and the basis of their classification have a brief idea of various statistical methods know the areas of applications of’ quantitative approach in business and management. Quantitative
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serving around 50 million people every day. All businesses face challenges every day. One of the major challenges facing McDonald’s is managing stock. Stock management involves creating a balance between meeting customers’ needs whilst at the same time minimising waste. Waste is reduced by: 1. Accurate forecasting of demand so that products do not have to be thrown away as often. 2. Accurate stock control of the raw materials. The Stock Management Problem How to Meet customer needs Minimise waste
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goal. At times it hard to pull this task off with just one location‚ imagine over 9‚000 locations spread all over the world. Starbucks is able to do something that nearly every franchise cannot do; they are able to keep quality inventory and a quality product no matter which location. They are able to keep quality inventory because all the locations are under one roof‚ while a franchise location is hit or miss depending on how much the franchisee cares about quality control. Time Series Data
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2009 2 c 2001-2009 Kevin Sheppard Contents Notes v 1 Included but not documented functions 1 2 Cross Sectional Analysis 5 2.1 Regression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.1.1 3 Regression: ols Stationary Time Series 3.1 ARMA Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Simulation: armaxfilter_simulate
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Production Planning Introduction The intention of this project is to demonstrate the function of production planning in a non - artificial environment. Through this simulation we are able to forecast‚ with a degree of certainty the monthly requirements for end products‚ subassemblies‚ parts and raw materials. We are supplied with information that we are to base our decisions on. The manufacturer depicted in this simulation was actually a General Electric facility that produced black and white
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IndividualWeek One Quiz | Resources: MyMathLab®Complete the Week One Quiz in MyMathLab®. | | 1 | Week Two: Business Applications | | Details | Due | Points | Objectives | 2.1 Solve simultaneous equations algebraically.2.2 Use time series data to forecast.2.3 Convert data to indices. | | | Readings | Read Ch. 12 of Prealgebra & Introductory Algebra.Read Topics 5 & 8 of Quantitative Reasoning. | | | Participation | Participate in class discussion. | | 2 |
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appropriate to conduct a time-series or cross sectional data. Evaluate the potential problems that may arise with your example and identify strategies for minimizing the impact of the potential problems. According to the text‚ Data collected for use in forecasting the value of a particular variable may be classified into two major categories - time series or cross sectional data. Time-series data are defined as a sequence of the values of an economic variable at different points in time. Cross-sectional
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method which best fits the needs of that organization. The forecasting needs and processes are different for each individual organization. Some companies will chose to maintain low inventory levels‚ opting for forecasting which focuses on shorter time periods; while other companies will need longer range forecasting due to maintaining higher inventory levels. Regardless of the needs‚ forecasting can be a useful tool for any company. We will look at objective and subjective forecasting methods
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fixed intervals of time‚ typically a year‚ month‚ week‚ or day. Answer Selected Answer: True Correct Answer: True Question 3 2 out of 2 points The Delphi method develops a consensus forecast about what will occur in the future. Answer Selected Answer: True Correct Answer: True Question 4 2 out of 2 points In regression models based on time-series data‚ the dependent variable is time or some function of time and the focus is
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