Consider the following time series data. Week123456Value19141612 1815 (a) Construct a time series plot.20202020181818161614-1412-1210-10108.8-6-6-4-442-212345612345613612456WeekWeekWeekWeekWhat type of pattern exists in the data?O The data appear to follow a horizontal pattern.O The data appear to follow a cyclical pattern.• The data appear to follow a seasonal pattern.O The data appear to follow a trend pattern.(b) Develop the three-week moving average forecasts for this time serles. (Round your answers to two dedimal places.)Time SeriesWeekForecastValue1192143164121615Compute MSE. (Round your answer to two decimal places.)MSE -What is the forecast for week 77Time Series Value

a) The correct answer is "Option B". On observing the graph, the data appear to be seasonal…

Answered: what type of pattern exists in the…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Consider the following time series data. Week 1 2 3 4 5 6 Value 19 11 16 10 17 12 (a) Construct a time series plot. 201 20 20 18 18- 18 18 16 16 14 2 2 4 6 7 1 2 4 6 7 2 4 5 6 2 4 6 Week Week Week Week What type of pattern exists in the data? The data appear to follow a horizontal pattern. The data appear to follow a seasonal pattern. O The data appear to follow a cyclical pattern. O The data appear to follow a trend pattern. (b) Develop the three-week moving average forecasts for this time series. (Round your answers to two decimal places.) Time Series Value Week Forecast 1 19 11 3 16 4 10 28.44 17 21.78 6 12 5.44 Compute MSE. (Round your answer to two decimal places.) MSE = 18.56 What is the forecast for week 7? 13
Consider the following time series data: 5 Month Value 1 36 2 19.5 8 30 9 4 18 10 28.5 11 6 34.5 12 7 22.5 13 For the naïve forecasting method and the MA2 forecasting method complete the following table: 14 15 Forecasting Method MAE MSE МАРЕ 16 Naïve 17 MA2 18 19 Based on the relative forecast error reported here which of the two forecasted methods would you choose. 20 21 22 23 24 25 26
Consider the following time series data: Using the naïve method (most recent value) as the forecast for the next week, compute thefollowing measures of forecast accuracy:a. Mean absolute errorb. Mean squared errorc. Mean absolute percentage errord. What is the forecast for week 7?
5
Respond to each of the items using the following time series data. Period Demand 1 104 2 132 3 117 4 120 5 104 6 141 7 120 8 136 9 109 10 143 11 142 12 109 13 113 14 124 15 113 16 107
(b) Using statistical software, develop a linear trend equation for this time series to forecast revenue (in $ billions). (Round your numerical values to four decimal places.) T₂ = 2.8450+ - 0.0124 X (c) Use the trend equation developed in part (b) to forecast retail store revenue (in $ billions) for 2018. (Round your answer to one decimal place.) $34.1 billion
QUESTION 8 Series A 300 250 200 150 100 50 1 2 3 4 5 6 7 8 9 10 11 12 13 Which forecasting method would be most appropriate for time series A? a. Winter's b. Holt's c. SARIMA
Consider the following time series data: Month 1 2 3 4 5 6 7 Value 24 12 20 11 19 24 16 (a) Compute MSE using the most recent value as the forecast for the next period. If required, round your answer to one decimal place. What is the forecast for month 8? If required, round your answer to one decimal place. Do not round intermediate calculation. (b) Compute MSE using the average of all the data available as the forecast for the next period. If required, round your answer to one decimal place. Do not round intermediate calculation. What is the forecast for month 8? If required, round your answer to one decimal place. (c) Which method appears to provide the better forecast? All Data average or Naiive
A statistical program is recommended. Annual retail store revenue for a technology company from 2007 to 2017 are shown below. Year Period 2007 Retail Store Revenue ($ billions) 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 35 30 25 20 15 10 35 30 25 20 15 10 5- 0- 1 (a) Construct a time series plot. + 2 3 4 0 1 2 5 6 7 8 9 10 11 Retail Store Revenue ($ billions) 30 25 20 WML 15 10 0 1 2 3 4 5 6 7 8 9 10 11 12 Period 3.915 3 4 6.110 6.777 9.280 14.327 19.028 20.428 21.662 28.309 26.998 30.703 5 6 Period 7 8 9 10 11 12 What type of pattern exists in the data? The time series plot shows a cyclical pattern. The time series plot shows a horizontal pattern. O The time series plot shows a downward trend. The time series plot shows an upward trend. o Retail Store Revenue ($ billions) 35 35 30 25 20 15 10 0 1 2 3 4 5 6 7 8 9 10 11 12 Period VV 5- 0- 0 1 2 3 4 5 6 7 8 9 10 11 12 Period A (b) Using statistical software, develop a linear trend equation for this time series to forecast revenue…
Consider the following time series data: Month 1 2 3 4 5 6 7 Value 25 13 19 11 19 23 16 (a) Compute MSE using the most recent value as the forecast for the next period. If required, round your answer to one decimal place. (b) Compute MSE using the average of all the data available as the forecast for the next period. If required, round your answer to one decimal place. Do not round intermediate calculation. What is the forecast for month 8? If required, round your answer to one decimal place.
Annual retail store revenue for a technology company from 2007 to 2017 are shown below. Year Period Retail Store Revenue ($ billions) 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 25 1 10 5+ 0 2 35 30 25 20 15 10 3 4 5 6 7 8 9 (a) Construct a time series plot. 10 11 Retail Store Revenue ($ billions) 0 1 2 3 3 3.915 4 4 5 6.110 5- 0- 0 1 2 3 4 5 6 6.777 9.280 14.327 19.028 20.428 21.662 и VM 28.309 26.998 30.703 5 6 7 8 9 10 11 12 Period 5 6 7 8 9 10 11 12 Period What type of pattern exists in the data? O The time series plot shows a cyclical pattern. O The time series plot shows a horizontal pattern. The time series plot shows a downward trend. The time series plot shows an upward trend. Q Retail Store Revenue ($ billions) 25 20 15- 10 5- 0 0 1 2 3 4 5 6 7 Period 35 30 25 20 M 5 0 0 1 2 3 4 5 6 7 8 9 10 11 12 Period 8 9 10 11 12 15 10 ↑ n (b) Using statistical software, develop a linear trend equation for this time series to forecast revenue (in $ billions). (Round your…
Consider the accompanying time series. a. Forecast the demand for each quarter in Year 4 using multiplicative decomposition. b. Interpret the meaning of the seasonal components. c. Calculate the MAD for this forecast. Click the icon to view the time series data table. Time Series Data Table Year 1 Quarter 1234 Demand 33 19 255 26 15 Quarter 1 2 3 A W 4 Year 2 Print Demand 26 18 25 8 Done Quarter 1 234 Year 3 2 Demand 28 15 23 5 n X

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