Project 2 data set

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Download the Data

The time series project will be based on the data set below.

Copy and run the code from the yellow box below to create the data sets:

data sales;
retain month;
input Week Day TotalSales OrdertypeA OrdertypeB OrdertypeC;
if _n_ <= 19 then month = 1;
else if _n_ <= 39 then month = 2;
else month = 3;
datalines;
1 4 539.577 61.543 175.586 302.448
1 5 224.675 38.058 56.037 130.58
1 6 129.412 21.826 25.125 82.461
2 2 317.12 41.542 113.294 162.284
2 3 210.517 37.679 56.618 116.22
2 4 207.364 30.792 50.704 125.868
2 5 263.043 43.304 66.371 153.368
2 6 248.958 38.584 85.961 124.413
3 2 344.291 33.973 148.274 162.044
3 3 248.428 36.399 43.306 168.723
3 4 281.42 45.706 111.036 124.678
3 5 243.568 43.851 66.277 133.44
3 6 308.178 43.339 136.434 128.405
4 2 363.402 46.241 120.865 196.296
4 3 336.872 56.519 136.709 143.644
4 4 246.992 56.167 78.101 112.724
4 5 308.88 51.66 92.272 164.948
4 6 233.126 47.717 71.474 113.935
5 2 404.38 59.135 157.681 187.564
1 3 298.56 90.476 80.509 127.575
1 4 229.249 42.904 43.962 142.383
1 5 236.304 47.331 72.444 116.529
1 6 297.174 32.077 127.358 137.739
2 2 409.401 58.721 139.034 211.646
2 3 231.035 36.017 75.813 119.205
2 4 238.826 35.576 79.997 123.253
2 5 235.598 54.401 75.613 105.584
2 6 242.112 37.656 59.907 144.549
3 2 490.79 57.81 236.248 196.732
3 3 289.657 43.359 89.382 156.916
3 4 298.459 45.555 148.718 104.186
3 5 323.603 45.55 120.548 157.505
4 3 616.453 67.884 267.342 281.227
4 4 346.035 70.376 154.242 121.417
4 5 307.645 71.068 100.544 136.033
4 6 253.847 64.137 109.062 80.648
5 2 530.944 118.178 260.632 152.134
5 3 333.359 51.199 124.66 157.5
5 4 306.356 47.002 99.892 159.462
1 6 416.83 109.888 131.165 175.777
2 2 415.187 77.388 154.863 182.936
2 3 268.002 46.295 96.87 124.837
2 4 234.503 53.366 69.15 111.987
2 5 234.724 47.399 77.61 109.715
2 6 230.064 48.081 72.826 109.157
3 2 357.394 59.042 130.098 168.254
3 3 259.246 44.809 99.072 115.365
3 4 244.235 39.025 110.74 94.47
3 5 402.607 39.6 240.922 122.085
3 6 255.061 57.467 88.462 109.132
4 2 342.606 41.418 135.189 165.999
4 3 268.64 34.193 115.536 118.911
4 4 188.601 32.653 81.576 74.372
4 5 202.022 51.985 51.93 98.107
4 6 213.509 36.748 71.353 105.408
5 2 316.849 59.131 92.639 165.079
5 3 286.412 54.224 115.746 116.442
5 4 303.447 58.378 142.382 102.687
5 5 304.95 76.763 96.478 131.709
5 6 331.9 107.568 121.152 103.18
;
run;

The SALES data set contains seven columns:

MONTH (1, 2, 3)
WEEK (1, 2, 3, 4, 5)
DAY (1-7)
TOTALSALES
ORDERTYPEA
ORDERTYPEB
ORDERTYPEC

The MONTH column contains the month number:

1 = first month
2 = second month
3 = third month

*Note: the exact month is not provided.

The WEEK column contains the week of the month:

1 = first week of the month
2 = second week of the month
... etc

The DAY column contains the day of the week.

1 = Sunday
2 = Monday
3 = Tuesday
...
7 = Saturday

The TOTALSALES column contains the total sales of the day.

The ORDERTYPEA, ORDERTYPEB and ORDERTYPEC contain the sales for order types A, B and C, respectively.

Note: the original data set is obtained from UCL machine learning repository:

Ferreira, R. P., Martiniano, A., Ferreira, A., Ferreira, A., & Sassi, R. J. (2016). Study on daily demand forecasting orders using artificial neural network. IEEE Latin America Transactions, 14(3), 1519-1525.

Not sure how to access the data in your SAS Studio? Please visit Data Set [9-14].

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