National mixer, Inc. sells can openers. Monthly sales for a seven-month period were as follows: Sales Month (000 units) Feb---- -19 March 18 April Мay 15 20 June- 18 July Aug.-------- 22 20 a. Forecast September sales volume using each of the following: 1. A five month-moving average 2. The naïve approach 3. A weighted using .60 for August, .30 for July, and .10 for June b. Which method seems least appropriate? And Why? c. What does use of the term sales rather than demand presume?
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- Q5) Monthly sales for a six month period are as follows: Month SalesJan 18,000Feb 22,000Mar 16,000Apr 18,000May 20,000June 24,000 Compute the sales forecast for July using the following approaches: (1) Four-month moving average; (2) Weighted three-month moving average using .50 for June, .30 for May and .20 for April;(3) Exponential smoothing with α (smoothing constant) equal to .40, assuming a February forecast of 18,000National Scan, Inc., sells radio frequency inventory tags. Monthly sales for a seven-month period were as follows: Month Sales (000 units)Feb. 19Mar. 18Apr. 15May 20Jun. 18Jul. 22Aug. 20 Forecast September sales volume using each of the following: (1)The naive approach. (2)A five-month moving average. (3)A weighted average using .60 for August, .30 for July, and .10 for June.V. Let's Explore / Let's Create 1. Discuss the other types of forecasting methods that financial analysts use to predict future revenues. 2. Are there any several other factors that may need to be considered that affects the sales forecast? RUBRIC Criteria Poor (3 Points) Fair (7 Points) Fair Good (10 Points) Good Deer
- Consider the following sales data for Bell, Inc. Month Sales ($ Millions) Jan. 10 Feb. 12 March 14 April 16 May 18 June 23 July 26 Aug. 31 Sept. 27 Oct. 18 Nov. 16 Dec. 14 a. Use a three-month weighted moving average to forecast the sales for the months April through December. Use weights of (3/6), (2/6), and (1/6), giving more weight to more recent data. b. Use exponential smoothing with α = 0.30 to forecast the sales for the months April through December. The forecast for January was $12 million. c. Compare the performance of the two methods by using the bias and MAD as the performance criteria. Which performance method is the most reasonable? Why?A weighted moving average using wl = 0.60; w2 = 0.30 and w3 = 0.10 Calculate MAD, MSE for each method and suggest the most appropriate method. C.b. Prepare forecasts for June through September by using an exponential smoothing model with α = 0.4. Assume that the forecast for May was 2,100 (enter your responses rounded to the nearest whole number). Month March April May June July August September March April May June Demand Demand 120 2,030 1,110 4,210 3,260 5,830 c. Prepare forecasts for June through September by using an adjusted exponential smoothing model with α = 0.4 and ß = 0.2. Assume that the unadjusted forecast for May was 2,100 and the trend factor T₁ for May was 900 (enter your responses rounded to the nearest whole number). Month 120 2,030 1,110 4,210 Forecast 2,100 1704 2707 2928 4089 2,100 1,704 Unadjusted forecast Adjusted forecast
- q10- What is the best description of Granger-causality? Select one: a. the ability of lags of one variable to contribute to the forecast of another variable b. the ability of a variable to predict its own future c. the ability of the one variable to explain it own past d. None of the above Clear my choice3. A mobile phone store owner wants to predict the demand for mobile phones in October based on the following historical sales data: Month- April May June. July August September Number of phones sold. 100, 140- 110. 150. 120. 160- a. What is this month's forecast using Naive approach b. Using 3-Month Moving Average, develop forecasts for October's demand c. Using 5-Month Moving Average, develop forecasts for October's demand d. When making moving average forecasts, is it better to use a larger time span? -22. Handy, Inc., produces a solar-powered electronic calculator that has experienced the following monthly sales history for the first four months of the year, in thousands of units: 23.3 March January February 30.3 72.3 April 15.5 a. If the forecast for January was 25, determine the one-step-ahead forecasts for February through May using exponential smoothing with a smoothing con- stant of a = .15. b. Repeat the calculation in part (a) for a value of a forecasts do you observe? c. Compute the MSES for the forecasts you obtained in parts (a) and (b) for February through April. Which value of a gave more accurate forecasts, based on the MSE? .40. What difference in the
- 4.6 The monthly sales for Telco Batteries, Inc., were as follows: Month Sales 20 January February March 21 15 14 April Мay 13 June 16 17 July August September October 18 20 20 November 21 December 23 a) Plot the monthly sales data. b) Forecast January sales using each of the following: i) Naive method. ü) A 3-month moving average. iii) A 6-month weighted average using .1, .1, .1, .2, .2, and .3, with the heaviest weights applied to the most recent months. iv) Exponential smoothing using an a = .3 and a September forecast of 18. v) A trend projection.Question 1 ) The monthiy sales Of yamizí Battery company are asfollows:- Month Jales 2000 2100 1500 1400 1300 Calcuiate fore cost sales for June using each of the fo llowing method: - i) Naive Method 1M 3 Month Simple moving averoger Ti) Exponentral smoothing using an a =0:3 cand may forecast of 1600 units.q1(a)Imagine that you need to introduce a new gadget such as the Apple Watch. Determine which forecasting method is appropriate for projecting the future demand of such this gadget. b)ARIMA is mostly used to forecast future values using historical time series data, as we all know. Its primary use is in short-term forecasting with at least 38-40 historical data points and a small number of outliers. If we don't have at least 38 data points, we should consider using another strategy.