Below is data of lobster sales volume from a seafood company. We are using exponential smoothing (α = 0.5) and 3-year moving average to forecast it. a. Please fill the blanks above and write your processes below. b. What are the mean absolute deviations (MADs) of the two methods? Which method will you choose based on the results?

Below is data of lobster sales volume from a seafood company. We are using exponential smoothing (α = 0.5) and 3-year moving average to forecast it. a. Please fill the blanks above and write your processes below. b. What are the mean absolute deviations (MADs) of the two methods? Which method will you choose based on the results?

Marketing

20th Edition

ISBN:9780357033791

Author:Pride, William M

Publisher:Pride, William M

Chapter6: Target Markets: Segmentation And Evaluation

Section: Chapter Questions

Problem 17DRQ: Under what conditions might a firm use multiple forecasting methods?

See similar textbooks

Similar questions

Under what conditions might a firm use multiple forecasting methods?
Given the following historical data, what is the simple three-period moving average forecast for period 6? Period Value 1 73 2 68 3 65 4 72 5 67
Following data on the demand for sewing machines manufactured by Taylor and Son Co. have been compiled for the past 10 years. Year 1971 1972 1973 1974 1975 78 1976 1977 1978 1979 99 1980 106 Demand 58 65 73 76 87 88 93 in (1000 units) Please estimate the value of demand for next 3 years using trend analysis.
The following table shows the three-period moving average and five-period moving average for monthly sales of Budget Furniture's during 2019. Moving averages of Budget Furniture's Time period Months Sales Three-period moving average (rounded off to Five-period moving average four decimals) R'millions 1 Jan 7 5.0000 6.2 February 5.6667 6.6 March 5 7.0000 B 4 April 8.3333 8.2 May 7 9.3333 8.4 June 8.3333 9.6 7 July 12 8.6667 9.6 August 4 A 9.2 September 10 10.6667 10 October 13 10.6667 11 November 9 12 December 10 The seasonal index for the month of February in 2019 is: LO
Font Paragraph Styles Question 3 Consider the following from an estate agent's business nationally: Month Houses Sold Jan Feb Mar 380 360 390 Apr May June July Aug Sep Oct 400 390 380 394 454 460 460 Nov Dec 430 370 a) Calculate the three point moving averages (quarters) and seasonal variation for the above data b) Define moving averages and how they're useful in forecasting (use Harvard referencing) c) At races, your horse, White Rum, has a probability of 1/20 of coming 1st, 1/10 of coming 2nd and a probability of 4 in coming 3rd. First place pays $5,000 to the winner, second place $4,000 and third place $1,350. Hence, is it worth entering the race if it costs $1050?
Based on the information in the following table, use the Exponential Smoothing Approach (a = 0.3) to forecast the demand for periods 4-13 %3D PERIOD MONTH Demand Forecast 1 Jan 222 Feb 192 222 3 Mar 212 213 Apr 202 May 220 Jun 200 7 Jul 113 Aug 175 6. Sep 277 10 Oct 211 11 Nov 249 12 Dec 144 13 Jan 6o 00
What is linear trend forecast.
ABC Inc. sells patio sets. Monthly sales for a seven-month period were as follows: Month Sales (000) Unites Feb 19 Mar 18 Apr 15 May 20 Jun 18 Jul 22 Aug 20 Forecast September sales volume using a five-month moving average approach.
ABC Inc. sells patio sets. Monthly sales for a seven-month period were as follows: Month Sales (000) Unites Feb 19 Mar 18 Apr 15 May 20 Jun 18 Jul 22 Aug 20 Forecast September sales volume using the naive approach.
Q1) Forecasting is both art and science. Describe the situations where we use Qualitative forecasting techniques and quantitative forecasting techniques
A newly operated company producing household items would want to forecast its sales volume for the next month. It has been in operation for ten (10) months now. For the past ten (10) months, forecast and sales data for its top selling Item A are as follow: Time Period Forecasted Value Actual Sales (Quantity) 10th month 405 345 9th month 400 380 8th month 410 400 7th month 370 375 6th month 330 360 5th month 320 325 4th month 320 315 3rd month 305 300 2nd month 290 295 1st month 300 280 The operations manager observes the fluctuations on the sales quantity over the 10-month period that the company is in operation. To forecast for the 11th month, the team decided to evaluate options on what forecasting method to use. Their options are: To use the Moving Average Method using the sales data for the past 10 months, To use the Exponential Smoothing Average assigning a smoothing constant of .6 and To use the Trend-adjusted Exponential Smoothing assigning smoothing constants α =…
Make a 15-year simple linear regression forecast. Example: Railroad Products Co. RPC Sales Car Loadings Year ($millions) (millions) 1 9.5 120 2 11.0 135 3 12.0 130 4 12.5 150 5 14.0 170 6 16.0 190 7 18.0 220