Using this dataset, create a multiple linear regression model that captures both
ID: 3361074 • Letter: U
Question
Using this dataset, create a multiple linear regression model that captures both linear trend and additive seasonality. You should use quarter one as your base season and fit the model with all 24 data points. (Do not include the variable ‘Major Promotions`.) Which of the following are TRUE?
If you add up all the error terms for this model, its value is -1.
If you add up all the error terms for this model, its value is 0.
If you add up all the error tems for this model, you generate the forecast for next year.
If you add up all the error terms for this model, its value is 1.
If you add up all the error terms for this model, its value is -1.
If you add up all the error terms for this model, its value is 0.
If you add up all the error tems for this model, you generate the forecast for next year.
If you add up all the error terms for this model, its value is 1.
Year Quarter Sales (US$ 000s) Major Promotions 2011 2011 2011 2011 2012 2012 2012 2012 2013 2013 2013 2013 2014 2014 2014 2014 2015 2015 2015 2015 2016 2016 2016 2016 76697 49302 57046 50142 2 2 50837 58424 48673 79571 53121 58818 50778 85228 54023 65755 51544 92149 60006 71542 56329 103243 64815 77070 60755 5 8 9 6 9 6 8Explanation / Answer
The sum of errors will always be 0 in case of a regression model. Hence,
If you add up all the error terms for this model, its value is 0.
Option B is correct.
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