2. Suppose that the University of the West had the following data of its growth of enrollment from2016-2014.YearEnrollment200630002007320020083600200936502010400020114200201243002013441020144520a. Forecast the 2015 enrollment using three-year weighted moving average forecast.b. Using smooth a = 0.30, forecast the 2015 enrollment.c. Using MAD, solve for the forecasting error at a = 0.10d. Use four-year weighted moving average from 2006-2015

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Answered: 2. Suppose that the University of the…

Practical Management Science

6th Edition

ISBN:9781337406659

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Publisher:WINSTON, Wayne L.

Chapter2: Introduction To Spreadsheet Modeling

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Problem 20P: Julie James is opening a lemonade stand. She believes the fixed cost per week of running the stand...

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9) Gasoline sales Times Series week sales (1000s of gallons 1 17 2 21 3 19 4 23 5 18 6 16 7 20 8 18 9 22 10 20 11 15 12 22 With the above gasoline time series data, show the exponential smoothing forecast using alpha = 0.1 i)Applying the MSE measure of forecast accuracy, would you prefer a smoothing constant of Alpha= 0.1 or alpha=0.2 for the gasoline sales time series? ii)Are the results the same if you apply MAE as the measure of accuracy? iii)What are the results if MAPE is used?
Café Michigan's manager, Gary Stark, suspects that demand for mocha latte coffees depends on the price being charged. Based on historical observations, Gary has gathered the following data, which show the numbers of these coffees sold over six different price values: D Price $2.50 $3.40 $2.10 $4.30 $3.00 $4.10 Using simple linear regression and given that the price per cup is $1.75, the forecasted demand for mocha latte coffees will be cups (enter your response rounded to one decimal place). Number Sold 765 515 975 245 315 480
Asvnch Problem - Statistical Forecasting Data Set – Eunice BC Fashion Monthly Sales, in million units. Year Total Sales Year Total Sales 2010 38 2016 43 2011 41 2017 40 2012 40 2018 45 2013 45 2019 47 2014 50 2020 42 2015 42 2021 48 Questions: a. Find the naïve forecast. b. Use the 3 years moving average forecast. c. Have a 5 years weighted moving average. d. Develop forecast using exponential smoothing with a = 0.2. e. Determine the trend line equation and present the forecast. f. Find the best forecast for year 2022. Note: Use the first 5 years as the training samples and the last 5 years as the forecasting samples. Solve it in Excel Sheet/Sheet with Equations as possible.
The number of patients coming to the Healthy Start Maternity clinic has been increasing steadilyover the past eight months. You are provided with some historical data as follows:Month Clinic attendance(in thousands)1 3.42 3.93 4.54 5.05 5.86 5.97 6.58 6.7b. Use simple linear regression to forecast annual demand for months 9 and 10 by using thetabular method to:-i. Derive the values for the intercept and slope. ii. Derive the linear regression equation. iii. Plot the linear regression line. iv. Develop a forecast of the clinic attendance for months 9 and 10.
Answer this using excel on a spreads
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tab s lock Mark Gershon, owner of a musical instrument distributorship, thinks that demand for guitars may be related to the number of television appearances by the popular group Maroon 5 during the month Ges collected the data shown in the following table V esc This exercise contains only parts b, c, and d. b) Using the least-squares regression method, the equation for forecasting is (round your responses to four decimal places): c) The estimate for guitar sales if Maroon 5 performed on TV 9 times = d) The correlation coefficient (r) for this model The coefficient of determination (2) for this model= The percentage of variation in sales that can be explained by TV appearances = Q A N @ 2 W S 31/1 X ** 3 8.0 F3 E D C $ Maroon 5 TV Appearances Demand for Guitars sales (round your response to two decimal places). (round your response to four decimal places). (round your response to four decimal places). 4 889 R F % 5 V d Es FS Y = T G % (round your response to two decimal places). A 6…
a. Use a 3-month moving average to estimate the month-in-advance forecast of demand for months 4–12 and generate a forecast for the first month of next year. Calculate the average forecast error and mean absolute error. b. Use a 3-month weighted moving average with weights of 0.6, 0.3, 0.1 (most recent to least recent, respectively) to calculate month-in-advance forecasts for months 4–12 and forecast for the first month of next year. Calculate the average forecast error and mean absolute error. c. Compare the average forecast error and MAD for the forecasting methods in parts a and b. Based on these error calculations, which of the two forecast methods would you recommend? Why?
Problem 3
2
Centerville Bikes and Stuff (CBS) sells motorcycles and accessories. The number of helmets sold by CBS per week for the past six weeks follows. Week 1 2 3 Value 18 13 (a) Construct a time series plot. 20T 18 16- 14- Time Series Value O Week 1 2 3 4 5 6 What type of pattern exists in the data? O The data appear to follow a cyclical pattern. O The data appear to follow a trend pattern. 8 6 O The data appear to follow a seasonal pattern. O The data appear to follow a horizontal pattern. Week 1 2 0 1 3 4 5 6 18 13 15 12 (b) Develop the three-week moving average for this time series. (Round your answers to two decimal places.) Time Series Value 16 14 18 + 2 13 15 4 5 6 15 12 16 3 Compute MSE. (Round your answer to two decimal places.) MSE = What is the forecast for week 7? 12 16 4 14 Week (c) Use a = 0.2 to compute the exponential smoothing values for the time series. Time Series Value 5 14 Forecast 6 Forecast 7 20 18 16 14 12 WE 10 2 + 7 @o 20 18 0 1 2 3 4 Week 5 6 00 0 1 2 3 4 5 Week 6 7…

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