Consider the following time series data:5MonthValue136219.583094181028.511634.512722.513For the naïve forecasting method and the MA2 forecasting method complete the following table:1415Forecasting MethodMAEMSEМАРЕ16Naïve17MA21819Based on the relative forecast error reported here which of the two forecasted methods would you choose.20212223242526

Suppose we have a certain number of years, and a certain number of values associated with the…

Consider the following time series data: Month Value 1 36 2 19.5 3 30 4. 18 5 28.5 34.5 22.5 For the naïve forecasting method and the MA2 forecasting method complete the following table: Forecasting Method МАЕ MSE МАРЕ Naïve MA2 Based on the relative forecast error reported here which of the two forecasted methods would you choose. 67

Consider the following time series data: Month Value 1 36 2 19.5 3 30 4. 18 5 28.5 34.5 22.5 For the naïve forecasting method and the MA2 forecasting method complete the following table: Forecasting Method МАЕ MSE МАРЕ Naïve MA2 Based on the relative forecast error reported here which of the two forecasted methods would you choose. 67

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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The variable week# is at what level of measurement
A statistical program is recommended. A company that sells musical instruments has been in business for five years. During that time, sales of pianos increased from 13 units in the first year to 77 units in the most recent year. The firm's owner wants to develop a forecast of piano sales for the coming year. The quarterly sales data follow. Year Quarter 1 Quarter 2 Quarter 3 Quarter 4 Total YearlySales 1 5 2 1 5 13 2 7 4 4 14 29 3 11 3 5 16 35 4 12 9 7 22 50 5 19 10 13 35 77 (a) Deseasonalize the data. (Round your answers to four decimal places.) Year Quarter Sales Adjusted Deseasonalized Seasonal Sales Index 1 1 5 1.3407 1 2 2 0.5998 1 3 1 0.4842 1 4 5 1.5753 2 1 7 1.3407 2 2 4 0.5998 2 3 4 0.4842 2 4 14 1.5753 3 1 11 1.3407 3 2 3 0.5998 3 3 5 0.4842 3 4 16 1.5753 4 1 12 1.3407 4 2 9 0.5998 4 3 7 0.4842 4 4 22 1.5753 5 1 19 1.3407 5 2 10 0.5998 5 3…
A statistical program is recommended. A company that sells musical instruments has been in business for five years. During that time, sales of pianos increased from 13 units in the first year to 77 units in the most recent year. The firm's owner wants to develop a forecast of piano sales for the coming year. The quarterly sales data follow. Year Quarter 1 Quarter 2 Quarter 3 Quarter 4 Total YearlySales 1 5 2 1 5 13 2 6 4 4 14 28 3 11 3 5 16 35 4 12 9 7 22 50 5 19 10 13 35 77 (a) Use the following dummy variables to develop an estimated regression equation to account for any seasonal and linear trend effects in the data: x1 = 1 if quarter 1, 0 otherwise; x2 = 1 if quarter 2, 0 otherwise; and x3 = 1 if quarter 3, 0 otherwise. (Let t = 1 denote the time series value in quarter 1 of year 1; t = 2 denote the time series value in quarter 2 of year 1; and t = 20 denote the time series value in quarter 4 of year 5. Round your numerical values to two decimal places.) t =…
The forecasts generated by two forecasting methods and actual sales have been collected in the Microsoft Excel Online file attached. Use the Microsoft Excel Online file attached to develop forecast accuracy and answer the following questions. 1. What is the MAD, the MSE, the MAPE, the RSFE, and the tracking signal for each forecasting method? Do not round intermediate calculations. Round your answers to two decimal places. Use the minus sign to enter negative values, if any. 2. What can be concluded about the quality of the forecasts 2? Assume that the control limit for the tracking signal is ±3. The results indicate (bias or no bias) in the forecasts 2, and that the tracking signal (is not or is) within the control limits of ±3.
Please answer part a, b, c, and d
Need a, b and c please
Untitled es Homework i https://ezto.mheducation.com/ext/map/index.html?_con=con&external_browser=0&launchUrl=http... A Period 1 2 X 345678 Syllabus-2210 X Bb 24689269 x Launch Meetin xAmazon.Com: x Group Me Demand 68 75 70 74 69 72 80 78 MAD F1 MAD F2 PREDICTED DEMAND F2 63 60 70 73 77 77 77 85 Two different forecasting techniques (F1 and F2) were used to forecast demand for cases of bottled water. Actual demand and the two sets of forecasts are as follows: F1 60 71 75 69 71 66 72 73 Click here for the Excel Data File Q Search c) www▪▪▪ Help Save & Exit 2 - x | + do Submit E 7:37 PM 8/23/2023
I don’t understand what to do with this table.
Week 1 2 3 4 5 6 Value 18 13 16 11 17 14 Using the naive method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy. d. What is the forecast for week 7 (to 2 decimals)?
A statistical program is recommended. A company that sells musical instruments has been in business for five years. During that time, sales of pianos increased from 12 units in the first year to 76 units in the most recent year. The firm's owner wants to develop a forecast of piano sales for the coming year. The quarterly sales data follow. Year Quarter 1 Quarter 2 Quarter 3 Quarter 4 1 2 3 4 5 4 7 11 12 18 2 4 forecast for quarter 2 forecast for quarter 3 forecast for quarter 4 3 9 10 1 4 5 7 13 5 14 16 22 35 Total Yearly Sales 12 29 35 50 76 (a) Use the following dummy variables to develop an estimated regression equation to account for any seasonal and linear trend effects in the data: x₁ = 1 if quarter 1, 0 otherwise; x₂ = 1 if quarter 2, 0 otherwise; and x3 = 1 if quarter 3, 0 otherwise. (Let t = 1 denote the time series value in quarter 1 of year 1; t = 2 denote the time series value in quarter 2 of year 1; ... and t = 20 denote the time series value in quarter 4 of year 5. Round…