uses actual sales from recent time periods to predict future sales‚ assuming each period has equal influence on the prediction of future sales‚ is the _____. Student Answer: moving average model weighted moving average model exponential smoothing model equal average model (TCO 3) Before performing linear regression‚ it is important to ensure that a linear relationship exists between the dependent and independent variables by plotting observed data on a diagram called the _____
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Research Objective 4 Background 4 Discussion on chosen topic 5 Discussion on current situation 7 Data analysis 8 Forecasting sales of Ice Cream Shop 8 Process of 3-Month moving average 9 3- Month Weighted moving average (1:2:3) 10 Exponential Smoothing (α= 0.1‚ α= 0.5) 11 Trend projections 13 Comparison of MAD‚ MSE and MAPE 15 EOQ Model 16 Recommendations 18
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of what will happen in the future n This is the main purpose of forecasting n Some firms use subjective methods n Seat-of-the pants methods‚ intuition‚ experience n There are also several quantitative techniques n Moving averages‚ exponential smoothing‚ trend projections‚ least squares regression analysis` © 2009 Prentice-Hall‚ Inc. 5–2 1 9/5/14 Introduction n Eight steps to forecasting : 1. Determine the use of the forecast—what objective are we trying to obtain? 2. Select the
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DEMAND FORECASTING The Context of Demand Forecasting The Importance of Demand Forecasting Forecasting product demand is crucial to any supplier‚ manufacturer‚ or retailer. Forecasts of future demand will determine the quantities that should be purchased‚ produced‚ and shipped. Demand forecasts are necessary since the basic operations process‚ moving from the suppliers’ raw materials to finished goods in the customers’ hands‚ takes time. Most firms cannot simply wait for demand to emerge and then
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These four techniques are called exponential smoothing‚ decomposition‚ ARIMA‚ and multiple regression. To do so I picked one dependent (Y) variable along with two independent (X) variables and collected 80 monthly observations for each variable. This historical data allowed me to create four different forecasting models which predict future Vehicle Sales with low risk of error. The best model according to the lowest error measures was winter’s exponential smoothing method because it had the lowest
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MgtOp 340 Exam 2 EOQ Suppose that JJ Inc. has a production rate of 250‚000 units per year and a demand of 800 per day. JJ has a setup cost of $40‚ and a holding cost percentage of 25%. JJ sells their product for $50 and it costs them $30 to produce it. If JJ works for 250 days per year‚ what is the optimal batch size? p=(250‚000/250days)=1‚000 P=250‚000(production rate) d=800 D=(800*250days)=200‚000 S=$40 I=.25 c=$30 H=(.25*30)=7.5 Optimal batch size => sqrt([2DS/H(1-d/p)]
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Demand Estimation Demand Curve Estimation ■ Simple Linear Demand Curves ■ The best estimation method balances marginal costs and marginal benefits. ■ Simple linear relations are useful for demand estimation. ■ Using Simple Linear Demand Curves ■ Straight-line relations give useful approximations. Identification Problem ■ Changing Nature of Demand Relations ■ Demand relations are dynamic. ■ Interplay of Supply and Demand ■ Economic
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There is a negative relationship. 3. On the plot labeled “b”‚ there is an outlier present. a. True b. False 4. On the plot labeled “c”‚ which of the following models is most appropriate? a. single-parameter exponential smoothing b. regression c. regression with seasonality (classical time-series) d. none of the above are appropriate 5. In a simple linear regression‚ we are using monthly advertising expenditures (in $000) to predict monthly profits
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The fixed and variable costs of each option can be evaluated by the tool with the consideration that all variable costs as a constant with the relationship between those two costs as linear and not exponential. The data used in this analysis was provided by Alistair Wu and Angela Down and using this information the volume was set to 1000 pairs of sneakers. The data received as outline above show that the cost to outsource would be 2 times that of reconditioning
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moving average‚ a three-year moving average‚ and exponential smoothing (with a w = 0.9 and a w = 0.3). The exponential smoothing forecasts may be begun by assuming Ŷt+1 = Yt. b. Using the forecasts from 2005 through 2009‚ compare the accuracy of each of the forecasting methods based on the RMSE criterion. c. Which forecast would you have used for 2010? Why? 5- year 3-Year Exponential Exponential Actual Moving Moving Smoothing Smoothing Year Demand Average Acverage (W= 0.9 ) (W= 0.3
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