Consider the time series data in Table 4 Construct a time series plot. What type of pattern exists in the data? Develop a three-week moving average for this time series. Compute MSE and a forecast for week 8. Use α = 0.2 to compute the exponential smoothing value for the time series. Compute MSE and a forecast for week 8.

The purpose of this assignment is to give you an opportunity to create a forecast based on data and interpret the results. You will also gain more practice with Minitab. Forecasting future commodity prices can be important for many production operations. One such commodity is the price of aluminum ($US per metric ton). For this assignment, you are asked to use Minitab to create two forecasts based upon the data provided below. First, create a one period forecast based upon a three month moving average. Second, create a one period forecast based upon exponential smoothing (using a smoothing weight of 0.95). Compare the two forecasts based upon the Mean Absolute Deviation (MAD) measure of accuracy. Interpret your results. The Data: Month Price Jan-18 2,209.73 Feb-18 2,181.79 Mar-18 2,069.24 Apr-18 2,254.69 May-18 2,299.67 Jun-18 2,237.62 Jul-18 2,082.24 Aug-18 2,051.51 Sep-18 2,026.46 Oct-18 2,029.86 Nov-18 1,938.51 Dec-18 1,920.38 Jan-19 1,853.72 Feb-19…

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 previous month. Gershon has collected the data shown in the following​ table:                                                                                                            Maroon 5 TV Appearances 3 4 8 6 7 7 Demand for Guitars 4 6 7 5 10 6   This exercise contains only parts​ b, c, and d. Part 2 ​b) Using the​ least-squares regression​ method, the equation for forecasting is ​(round your responses to four decimal ​places)​:   Y​ = enter your response here ​+ enter your response herex

Develop a forecast for the next month using a four-month moving average method. Use the Excel Functions SLOPE and INTERCEPT to write the linear regression prediction equation with Months as the independent variable and sales as the dependent variable. Use the prediction equation to estimate the number of sales in month 9.

Elna inc is a microwave manufacturing and distribution company based in Jakarta. The company needs to estimate production demand using the historical sales data of the last 24 months (periods).A logistics manager of the company then uses the moving average, exponential smoothing, and simple linear regression methods to determine sales forecasts for the next 12 months (Graphically illustrate the results). Provide an analysis and the results of bias, MAPE, MSE, and MAD for the forecasting decisions.Moving average is 4 month, and alfa is 0.05

Y9

A company wants to generate a forecast for unit demand for year 2017 using exponential smoothing. The actual demand in year 2016 was 120. The forecast demand in year 2016 was 110. Using this data and a smoothing constant alpha of 0.1, which of the following is the resulting year 2017 forecast value?

Harlen Industries has a simple forecasting model: Take the actual demand for the same month last year and divide that by the number of fractional weeks in that month. This gives the average weekly demand for that month. This weekly average is used as the weekly forecast for the same month this year. This technique was used to forecast eight weeks for this year, which are shown in the following tables along with the actual demand that occurred. The following eight weeks show the forecast (based on last year) and the demand that actually occurred (picture attached): Calculate the MAD and tracking signal for each week.

The problem below looks at forecasting methodologies to determine which forecasting model results in the most accurate forecasts.  Accuracy is determined by the lowest mean absolute deviation.   Emergency calls to the 911 system of York County for the past 24 weeks are shown below.  Accurate forecasts are needed to determine the number of operators needed to staff the station.    Week # of Calls 1 50 2 35 3 25 4 40 5 45 6 35 7 20 8 30 9 35 10 20 11 15 12 40 13 55 14 35 15 25 16 55 17 55 18 40 19 35 20 60 21 75 22 50 23 40 24 65 1. WEIGHTED MOVING AVERAGE Using an averaging period of 3 with the most recent period weighted .5, the next most recent .4, and the oldest period weighted .1, forecast weeks 4 through 24.  Calculate the MAD for this forecasting model. Show your work in a table like the one below Indicate which model is…

Please do not give solution in image formate thanku. The Willow River Mining Company mines and ships coal. It has experienced the following demand for coal during the past eight years: Year Coal Sales (tonnes) 1 4260 2 4510 3 4050 4 3720 5 3900 6 3470 7 2890 8 3100 Develop an adjusted exponential smoothing model (α=0.30, β=0.20) and a linear trend line model, and compare the forecast accuracy of the two using MAD. Indicate which forecast seems to be most accurate.