Name: Directions: * The following software may be used: * Excel->Data Analysis * Excel QM * QM for Windows (PC only) * Please make sure to insert your answers, including any charts, graphs, or output, on this document. You may be required to also upload original files from Excel or QM for Windows. * The calculations are not your final answer. A summary/explanation in your own word for each question posed should be included. * Question 6 requires the use
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equation for the linear trend component for the time series. b. Use the developed linear trend equation to forecast for the years 8, 9 and 10 based on the equation. c. What is the average increase in the sales per year for the stall? d. Calculate forecasted demand for books using three-year moving average method. e. Calculate Mean
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| (A): find 3 period and 4 period moving average for given data by comparing both averages and interpret which average is best for the company? Quarters | Demand | Moving average 3 quarters | Moving average 4 quarters | 1 | 64 | | | 2 | 71 | | | 3 | 58 | 63 | | 4 | 32 | 45 | 63 | 5 | 46 | 43 | 45 | 6 | 78 | 43 | 43 | 7 | 81 | 88 | 43 | 8 | 66 | 72 | 88 | Interpretation: while using movinf average method, 3 quarters Moving average is more closest and accurate for company
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to be any type of pattern or correlation, negative or positive. B) Starting in year 4 and going to year 12, forecast demand using a 3-year moving average. Plot your forecast on the same graph as the original data. It looks to me as if the rise is steady C) Starting in year 4 and going to year 12, forecast demand using a 3-year moving average with weights of .1, .3, and .6, using .6 for the most recent year. Plot this forecast on the same graph. So the weighted forecast is quite the
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4.9 (a, b) The computations for both the two- and three-month averages appear in the table; the results appear in the figure below. [pic] (c) MAD (two-month moving average) = .750/10 = .075 MAD (three-month moving average) = .793/9 = .088 Therefore, the two-month moving average seems to have performed better. |Table for Problem 4.9 (a, b, c) | | | | |Forecast
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previous value of a time series as the basis of a forecast. [pic] Techniques for Averaging • What is the purpose of averaging? • Common Averaging Techniques o Moving Averages o Exponential smoothing Moving Average [pic] Exponential Smoothing [pic] Techniques for Trend Linear Trend Equation [pic] [pic]
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CHAPTER = 11 Q-1 | | |Factor |Factor Score for Each Location | | |Location Factor |Weight |A |B |C |D | | |1. Labor climate | 5 |5 | | |Location Factor |Weight |A |B
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Sales Volume 10000 12400 14250 15750 20500 18500 15750 20500 21500 22550 6. Using Data Set E1, what would be the forecast for period 7 using a four period moving average: (Choose the closest answer.) a. 17625 b. 15225 c. 15300 d. 17250 7. Using Data Set E1, what would be the forecast for period 6 using a five period weighted moving average? The weights for each period are 0.05,
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stable situations: Existing products, technology. Time-series Models: Naïve approach, Moving averages, Exponential smoothing. Associative (regression) Methods: Simple regression (trend projection if x=t) ,Multiple regression. Average completion time: Total flow time/Number of jobs/Utilization =Total job work time/Total flow time Average number of jobs in the system=Total flow time/Total job work time/Average job lateness =Total late days/Number of jobs CR=Time remaining to due date/Shop time
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Financial Time Series Analysis Jiajing Sun University of Chinese Academy of Sciences 22 September 2013 J. Sun (UCAS) ARMA(1) 22 September 2013 1 / 23 Review As pointed out in the last week, the objective of studying …nancial time series analysis is to predict future values of some …nancial variable. This objective is achieved by following methodology based on: 1 2 3 4 Model Speci…cation; Model Estimation; Model Validation; Forecasting (or prediction) Note: The model
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