Run a multiple regression with trend and seasonal; forecast the next 12 months. year Month...

Run a multiple regression with trend and seasonal; forecast the next 12 months.

year	Month	Crates
1999	Jan	20400
	Feb	13600
	Mar	17000
	Apr	30600
	May	23800
	Jun	17000
	Jul	27200
	Aug	30600
	Sep	34000
	Oct	45900
	Nov	40800
	Dec	30600
2000	Jan	13600
	Feb	23800
	Mar	30600
	Apr	25500
	May	27200
	Jun	30600
	Jul	23800
	Aug	47600
	Sep	37400
	Oct	45900
	Nov	44200
	Dec	17000
2001	Jan	20400
	Feb	13600
	Mar	30600
	Apr	22100
	May	23800
	Jun	30600
	Jul	28900
	Aug	34000
	Sep	42500
	Oct	47600
	Nov	30600
	Dec	30600
2002	Jan	25500
	Feb	20400
	Mar	23800
	Apr	30600
	May	25500
	Jun	30600
	Jul	34000
	Aug	37400
	Sep	44200
	Oct	47600
	Nov	34000
	Dec	37400
2003	Jan	25500
	Feb	37400
	Mar	30600
	Apr	30600
	May	27200
	Jun	34000
	Jul	47600
	Aug	47600
	Sep	34000
	Oct	51000
	Nov	37400
	Dec	47600

Expert Solution

ANSWER:

Let me first give you the description of each of the dummy variable.

Dummy_Jan= Binary if month is Jan
Dummy_Feb= Binary if month is Feb
Dummy_Mar= Binary if month is Mar
Dummy_Apr= Binary if month is Apr
Dummy_May= Binary if month is May
Dummy_Jun= Binary if month is Jun
Dummy_Jul= Binary if month is Jul
Dummy_Aug= Binary if month is Aug
Dummy_Sep= Binary if month is Sep
Dummy_Oct= Binary if month is Oct
Dummy_Nov= Binary if month is Nov
Dummy_Dec= Binary if month is Dec

Now, after putting the variables in the regression, we get the model as above:

Crates = 32460-11560*Dummy_Jan-10880*Dummy_Feb-6120.00000000001*Dummy_Mar-4759.99999999999*Dummy_Apr-7139.99999999999*Dummy_May-4080*Dummy_Jun-339.999999999997*Dummy_Jul+6800.00000000001*Dummy_Aug+5780*Dummy_Sep+14960*Dummy_Oct+4760.00000000001*Dummy_Nov

Value of F-Statistic = 6.9 an significance = 0.0000008 << 0.05, so at 5% level of significance the model is important.

The R-adj = 52.38% and R-sq = 61.26%, which implies around 62% of the total variability of the dependent variable is explained by the model.

milcah answered 1 month ago

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