Forecast the 5th year all 4 quarters using Additive decomposition model.(Hint:intercept=15.1495, slope=0.1461 of deseasonalized data after linear regression.). Calculate theRMSE and MAPE.tQuarter SalesYear(1000s)1Year 1114.82214.13316.016.55Year 2115.86215.27316.88417.49Year 311610215.6111234317.5417.813Year 4116.31415161718567823215.9318.0418.4Year 511920234

Step 1: Let's perform these steps:1. Calculate Seasonal IndicesTo calculate seasonal indices, we…

Answered: Forecast the 5th year all 4 quarters…

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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Using the regression to model annual income, a variable for years of education has a slope = 2000. This means that the model predicts each additional year of education will yield an extra 2,000 for the average person's salary, regardless of how many total years of education a person has. A. True B. False
Develop a scatterplot and explore the correlation between customer age and net sales by each type of customer (regular/promotion). Use the horizontal axis for the customer age to graph. Find the linear regression line that models the data by each type of customer. Round the rate of changes (slopes) to two decimal places and interpret them in terms of the relation between the change in age and the change in net sales. What can you conclude? Hint: Rate of Change = Vertical Change / Horizontal Change = Change in y / Change in x
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9 students were surveyed to see what their age is and what their income level is. Find the equation of the line using linear regression. We want to predict their age using their income. age 18 24 38 22 19 35 28 19 27 income 456 786 835 855 645 244 587 1400 975 Just a side note, the 19 year old is making 1400, would be considered an outlier since they are making way more than everyone else. (y=-.0061x+34.9874 4 decimals) y=30.3709-.0064

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