TYPO*** the question is for the past 3 years***

F3 F1 36.8 35.3 Name A B D E F G F2 13.8 13.2 13.2 13.7 14.4 13.9 16.1 15.1 15.8 12.9 16.1 13.6 12.9 12.7 $72,245 $70,639 $64,879 $75,591 $80,615 $76,507 $107,935 $82,557 $88,041 $64,597 34.8 39.3 36.6 35.7 40.5 43.1 37.7 40.4 33.8 36.2 39.1 39.4 36.1 35.3 36.6 34.4 38.1 37.9 1 J K L M N O P Q R S T ZZ Balance $35,206 $33,434 $28,162 $36,708 $38,766 $34,811 $41,032 $41,742 $51,107 $34,936 $32,150 $37,996 $26,785 $32,576 $56,569 $26,144 $24,558 $34,811 $26,773 $24,890 $40,550 $76,771 $53,713 $60,262 12.8 12.7 13.9 12.8 12.7 13.5 $48,600 $51,419 $76,507 $60,753 $47,388 $67,500 (b). Given quarterly sales data for the past 5 years, as shown below, copy-paste(or snip) the Excel worksheet that correctly identify all the columns/ fields and the data (rows) that must be used in , to correctly capture the trend and seasonality in the dataset, in order to obtain a linear regression model to predict the sales. (Note : No need to run regression, no need to find optimal model). + Month Year 1 Year 2 Year 3 Quarter 1 ($100,000s) 5.12 5.24 5.36 Quarter 2 ($100,000s) 4.92 4.98 4.98 Quarter 3 ($100,000s) 4.49 4.59 4.63 Quarter 4 ($100,000s) 4.55 4.58 4.61 F3 F1 36.8 35.3 Name A B D E F G F2 13.8 13.2 13.2 13.7 14.4 13.9 16.1 15.1 15.8 12.9 16.1 13.6 12.9 12.7 $72,245 $70,639 $64,879 $75,591 $80,615 $76,507 $107,935 $82,557 $88,041 $64,597 34.8 39.3 36.6 35.7 40.5 43.1 37.7 40.4 33.8 36.2 39.1 39.4 36.1 35.3 36.6 34.4 38.1 37.9 1 J K L M N O P Q R S T ZZ Balance $35,206 $33,434 $28,162 $36,708 $38,766 $34,811 $41,032 $41,742 $51,107 $34,936 $32,150 $37,996 $26,785 $32,576 $56,569 $26,144 $24,558 $34,811 $26,773 $24,890 $40,550 $76,771 $53,713 $60,262 12.8 12.7 13.9 12.8 12.7 13.5 $48,600 $51,419 $76,507 $60,753 $47,388 $67,500 (b). Given quarterly sales data for the past 5 years, as shown below, copy-paste(or snip) the Excel worksheet that correctly identify all the columns/ fields and the data (rows) that must be used in , to correctly capture the trend and seasonality in the dataset, in order to obtain a linear regression model to predict the sales. (Note : No need to run regression, no need to find optimal model). + Month Year 1 Year 2 Year 3 Quarter 1 ($100,000s) 5.12 5.24 5.36 Quarter 2 ($100,000s) 4.92 4.98 4.98 Quarter 3 ($100,000s) 4.49 4.59 4.63 Quarter 4 ($100,000s) 4.55 4.58 4.61