and/or with finding the solutions of an equation. HISTORICAL OBJECTIVES 1. attempts to deal with problems devoted to finding the values of one or more unknown quantities. 2. the evolution of the notion of number 3. the gradual refinement of a symbolic language THE SEARCH OF “EQUATION” • Egyptian Mathematics Egyptian mathematical texts known to us dated from about 1650 B.C. • They attest for the ability to solve problems equivalent to a linear equation in one unknown • Later evidence‚ indicates
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Executive summary…………………………………………………………………………………4 2.0 Introduction……………………………………………………………………………………………5 3.0 Question 1……………………………………………………………………………………………...6 4.1 a) Time series plot…………………………………………………………………………6 4.2 b) Exponential smoothing methods……………………………………………….8 4.3 c) 8 months Forecasted period……………………………………………………11 4.4 d) Forecasting report……………………………………………………………………13 4.0 Question 2…………………………………………………………………………………………….15 5.5 Forecasting
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Relationship (Monotonically • Understand that a Power Law Relationship requires that the Logarithm be taken for “Both” sides of the Equation and results in the Logarithm being taken for both Variables • Be able to convert Bivariate Data that fits a Power Law Relationship into a set of Linear Bivariate Data • Be able to create a Linear Form Predictor Equation for Bivariate Data that is Power Law and be able to predict new data values for the original Power Law Data Decreasing has an Inverse
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MGMT 472 Homework assignment 2 1. According to the text‚ key ingredients for developing successful supply partnerships include all of the following EXCEPT: a. Personal relationships b. Individualized objectives c. Mutual benefits and needs d. Performance metrics 2. The combination of the purchase price of a good and additional costs incurred before or after product delivery can be referred to as: a. Total cost of acquisition b. Total cost of ownership c. Purchase requisition cost d. Total procurement
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however‚ environmental regulations became more relaxed in spite of the mounting evidence for global climate change. 2. Explain the main point concerning exponential growth and whether it is good or bad. Compare exponential growth to a logistic growth curve and explain how these might apply to human population growth. What promotes exponential growth? What constrains population growth? The population growth is dependent and thus proportional to the birth rate‚ which is the main variable.
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3101 MSOM 3rd in-class Group Assignment (Mod B and Ch 4) Q1) 39) A linear programming problem that aims to minimize cost‚ has two constraints 2X + 4Y ≥ 100 and 1X + 8Y ≤ 100. Which of the following statements about its feasible region is true? (2-points) A) There are four corner points including (50‚ 0) and (0‚ 12.5). B) The two corner points are (0‚ 0) and (50‚ 12.5). C) The feasible region is triangular in shape‚ bounded by (50‚ 0)‚ (33-1/3‚ 8-1/3)‚ and (100‚ 0). D) The graphical origin (0‚ 0)
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past patterns in data can be used to forecast future data points. 1. Moving averages (simple moving average‚ weighted moving average): forecast is based on arithmetic average of a given number of past data points 2. Exponential smoothing (single exponential smoothing‚ double exponential smoothing) - a type of weighted moving average that allows inclusion of trends‚ etc. 3. Mathematical models (trend lines‚ log-linear
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the naïve method‚ a two-period movingaverage‚ and exponential smoothing with an α = 0.2. (Hint: Use naïve to start the exponentialsmoothing process.)MonthSales Naïveb) Compare the forecasts using MAD and decide which is best.Exponential = MAD = Σ | actual – forecast | = 13.73 8+8+4+7/4= 6.75nNaïve = MAD = Σ | actual – forecast | = 8.25 10+10+5+8/4= 8.25n2 period = MAD = Σ | actual – forecast | = 8.25 2.5+15+10+8/4= 8.25nAnswer: Exponential is bestc) Using your method of choice‚ make a forecast
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planning‚ production planning and budgeting‚ cash budgeting‚ analyzing various operating plans. 6. There is no mechanism for growth in these models; they are built exclusively from historical demand values. Such methods will always lag trends. 7. Exponential smoothing is a weighted moving average where all previous values are weighted with a set of weights that decline exponentially. 8. MAD‚ MSE‚ and MAPE are common measures of forecast accuracy. To find the more accurate forecasting model‚ forecast
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1150 1087 1170 1196 1084 2008 1270 1137 1170 1155 1104 2009 1290 1186 1207 1259 1154 2010 x 1214 1236 1287 1195 B) Five-year moving average = 141.9 Three-year moving average = 78.6 Exponential smoothing (w = .9) = 45.7 Exponential smoothing (w = .3) = 110.9 C) I would use the exponential smoothing w=.9 because of the trending factor 6) A) In 2010 = 11450 units B) Sales would go from 11450 to 1100‚ which is about 3.9% reduction/loss C) Sales would decrease from 11450 to 9650
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