1. Plot the time series (Sheet: Data) of your related region (Table 2).

2. Identify the adapted method for your region.

3. Make a forecasting for the region based on the adapted model

4. What are the best parameters of your proposed model ?

5. What are the parameters for the worst model ?

6. What will be the forcasted value of january 2022 ?

7. Propose a method for taking into accound the random component.

8. Based on your new model, plot your forcasted time series

9. What will be the new forcasted value of january 2022 ?

10. Comment your results

Month	Region 7
Jan-18	60000
Feb-18	77184
Mar-18	77885
Apr-18	86190
May-18	96117
Jun-18	97143
Jul-18	84757
Aug-18	79804
Sep-18	64800
Oct-18	59307
Nov-18	52157
Dec-18	45049
Jan-19	58627
Feb-19	76200
Mar-19	82871
Apr-19	84904
May-19	93100
Jun-19	93000
Jul-19	83048
Aug-19	74854
Sep-19	60769
Oct-19	55619
Nov-19	48155
Dec-19	42647
Jan-20	57885
Feb-20	77647
Mar-20	81845
Apr-20	86095
May-20	91776
Jun-20	100680
Jul-20	86190
Aug-20	71887
Sep-20	60000
Oct-20	55566
Nov-20	50857
Dec-20	42596
Jan-21	58095
Feb-21	75566
Mar-21	80286
Apr-21	85140
May-21	90093
Jun-21	95472
Jul-21	87308
Aug-21	74476
Sep-21	61698
Oct-21	57238
Nov-21	50673
Dec-21	51238
Jan-22	59712
Feb-22	77961
Mar-22	83725
Apr-22	90297
May-22	91143
Jun-22	99320
Jul-22	93922
Aug-22	73143
Sep-22	66699
Oct-22	56476
Nov-22	51068
Dec-22	46893