a) Calculate the 3-month Moving Average Forecast for sales from April/2019 to Januar enter them in the table above. b) Calculate MAD, MSE and MAPE for the forecast obtained from April/2019 to January/20 oblem #3- At Freeze Inc. the manufacturing of each air conditioning has a variable cost of $500 per unit ace in a facility that has a monthly fixed cost of $250,000. If Freeze Inc. sells each unit at $1,000, how many units do they need to sell every month to b What is the monthly revenue at the break-even point? What is the monthly variable cost at the break-even point? What is the total operating cost at the break-even point? If Freeze Inc. sells 600 units at $1,000 each on a given month, calculate the profit.
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- Play Things is developing a new Lady Gaga doll. The company has made the following assumptions: The doll will sell for a random number of years from 1 to 10. Each of these 10 possibilities is equally likely. At the beginning of year 1, the potential market for the doll is two million. The potential market grows by an average of 4% per year. The company is 95% sure that the growth in the potential market during any year will be between 2.5% and 5.5%. It uses a normal distribution to model this. The company believes its share of the potential market during year 1 will be at worst 30%, most likely 50%, and at best 60%. It uses a triangular distribution to model this. The variable cost of producing a doll during year 1 has a triangular distribution with parameters 15, 17, and 20. The current selling price is 45. Each year, the variable cost of producing the doll will increase by an amount that is triangularly distributed with parameters 2.5%, 3%, and 3.5%. You can assume that once this change is generated, it will be the same for each year. You can also assume that the company will change its selling price by the same percentage each year. The fixed cost of developing the doll (which is incurred right away, at time 0) has a triangular distribution with parameters 5 million, 7.5 million, and 12 million. Right now there is one competitor in the market. During each year that begins with four or fewer competitors, there is a 25% chance that a new competitor will enter the market. Year t sales (for t 1) are determined as follows. Suppose that at the end of year t 1, n competitors are present (including Play Things). Then during year t, a fraction 0.9 0.1n of the company's loyal customers (last year's purchasers) will buy a doll from Play Things this year, and a fraction 0.2 0.04n of customers currently in the market ho did not purchase a doll last year will purchase a doll from Play Things this year. Adding these two provides the mean sales for this year. Then the actual sales this year is normally distributed with this mean and standard deviation equal to 7.5% of the mean. a. Use @RISK to estimate the expected NPV of this project. b. Use the percentiles in @ RISKs output to find an interval such that you are 95% certain that the companys actual NPV will be within this interval.The owner of a restaurant in Bloomington, Indiana, has recorded sales data for the past 19 years. He has also recorded data on potentially relevant variables. The data are listed in the file P13_17.xlsx. a. Estimate a simple regression equation involving annual sales (the dependent variable) and the size of the population residing within 10 miles of the restaurant (the explanatory variable). Interpret R-square for this regression. b. Add another explanatory variableannual advertising expendituresto the regression equation in part a. Estimate and interpret this expanded equation. How does the R-square value for this multiple regression equation compare to that of the simple regression equation estimated in part a? Explain any difference between the two R-square values. How can you use the adjusted R-squares for a comparison of the two equations? c. Add one more explanatory variable to the multiple regression equation estimated in part b. In particular, estimate and interpret the coefficients of a multiple regression equation that includes the previous years advertising expenditure. How does the inclusion of this third explanatory variable affect the R-square, compared to the corresponding values for the equation of part b? Explain any changes in this value. What does the adjusted R-square for the new equation tell you?The following table represents sales data for milk (in hundred liters) sold by a grocery.Do the computations to fill out the table and answer the following questions:1. Using MAD as the criterion, which of the following models would you use for thegiven time series data? Why?A. Naïve approach;B. 5-month SMA model;C. WMA model with weights 0.1, 0.3, and 0.6; orD. ES model with α = 0.5 and a forecast of 3,500 liters in the first month.NOTE: In answering Item 1, mention the whole description of the model; i.e., not just“SMA model”, but “SMA model with n = ...”; not just “WMA model”, but “WMA modelwith weights ...”; not just “ES model”, but “ES model with α = ...”.2. Interpret the MAD of the most accurate among the forecasting models above.3. Based on your decision in Item 1, what should be the forecast for Month 11?
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- The following time series shows the sales of a particular product over the past 12 months. Month Sales 1 105 2 135 3 120 4 105 5 90 6 120 7 145 8 140 9 100 10 80 11 100 12 110 (a)Use ? = 0.4 to compute the exponential smoothing values for the time series. (Round your answers to two decimal places.) Month t Time Series Value Yt Forecast Ft 1 105 2 135 3 120 4 105 5 90 6 120 7 145 8 140 9 100 10 80 11 100 12 110 (b)Use a smoothing constant of ? = 0.6 to compute the exponential smoothing forecasts. (Round your answers to two decimal places.) Month t Time Series Value Yt Forecast Ft 1 105 2 135 3 120 4 105 5 90 6 120 7 145 8 140 9 100 10 80 11 100 12 110Macomb Inc. used Excel to run a least-squares regression analysis on the production cost data resulting in the following output: Regression StatisticsMultiple R 0.9834 R Square 0.9596 Observations 30 Coefficients Standard Error T Stat P-ValueIntercept 174,980 61,580 2.84 0.021 Production units (X) 11.53 0.9265 12.44 0.000 What total cost would Macomb predict for a month in which production is 2,000 units? Multiple Choice $174,900 $63,433 $198,040 $23,037As a demand planner at Grootegeluk Mine, you want to determine the monthly sales forecast of coal (in tonnes). Table 1, below, depicts the volume of coal sold by the mine for each of the 12 months of 2022.Table 1: Volume of coal sold monthly during 2022 Year Monthly volume (tonne s) Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2022 21 23 34 37 40 51 54 50 48 36 39 42 1. Using the three-month weighted moving average method, calculate the monthly forecasts for April 2022 to January 2023 by assigning weights of 0.1, 0.3, and 0.6 (the oldest data to the most recent data, respectively) (Round off forecast values to one decimal place). 2. Calculate the mean absolute deviation (MAD) of the forecasts for April 2022 to December 2022 (Round off the answer to two decimal place). 3.
- Camille forecasts to sell 575 units of the perfume she is selling by the first week of December. At the end of the 1st week of December, she was able to disposed 500 perfumes at Php150 each. Of these 500 units, she gave a total of 20 giveaways. The total cost for each perfume is Php120. Determine Camille’s net sales volume. *4802075500 Let’s say that last November you have sold 10,000 pieces of chrysanthemum at 25 pesos each. For every piece sold, you will be given a commission of 10%. How much was your total commission? *225,00025,00010,0002.50250,000The table below shows the sales figures for a brand of shoe over the last 12 months.Months SalesJanuary 69February 75March 86April 92May 95June 100July 108August 115September 125October 131November 140December 150a. Using the following, forecast the sales for the months up to January the following year:-i. A simple three month moving average. ii. A three period weighted moving average using weights of 1, 2 and 3. Assign the highest weight to the most recent data. iii. Exponential Smoothing when α= .6 and the forecast for March is 350.iv. Determine which of the three forecasting technique is the most accurate using MAD.A manager uses this equation to predict demand for landscaping services: Ft = 14 + 4t. Over the past eight periods, demand has been as follows: Period, t: 1 2 3 4 5 6 7 8 Demand: 20 25 25 35 35 40 45 50 Compute the tracking signals for Periods 1-8. (Negative values should be indicated by a minus sign. Round your intermediate calculations and final answers to 3 decimal places.) Period t Tracking Signal 1 2 3 4 5 6 7 8