Question
Month Year Sales Jan 2014 1489 Feb 2014 1292 Mar 2014 1351 Apr 2014 1263 May 2014 1205 Jun 2014 1093 Jul 2014 1255 Aug
Month | Year | Sales |
Jan | 2014 | 1489 |
Feb | 2014 | 1292 |
Mar | 2014 | 1351 |
Apr | 2014 | 1263 |
May | 2014 | 1205 |
Jun | 2014 | 1093 |
Jul | 2014 | 1255 |
Aug | 2014 | 1699 |
Sep | 2014 | 1392 |
Oct | 2014 | 1248 |
Nov | 2014 | 1163 |
Dec | 2014 | 1389 |
Jan | 2015 | 1432 |
Feb | 2015 | 1221 |
Mar | 2015 | 1194 |
Apr | 2015 | 1163 |
May | 2015 | 1103 |
Jun | 2015 | 1056 |
Jul | 2015 | 1160 |
Aug | 2015 | 1586 |
Sep | 2015 | 1314 |
Oct | 2015 | 1148 |
Nov | 2015 | 1073 |
Dec | 2015 | 1285 |
Jan | 2016 | 1247 |
Feb | 2016 | 1136 |
Mar | 2016 | 1171 |
Apr | 2016 | 1099 |
May | 2016 | 1060 |
Jun | 2016 | 982 |
Jul | 2016 | 1026 |
Aug | 2016 | 1544 |
Sep | 2016 | 1251 |
Oct | 2016 | 1032 |
Nov | 2016 | 1007 |
Dec | 2016 | 1169 |
Jan | 2017 | 1228 |
Feb | 2017 | 1004 |
Mar | 2017 | 1096 |
Apr | 2017 | 953 |
May | 2017 | 996 |
Jun | 2017 | 930 |
Jul | 2017 | 962 |
Aug | 2017 | 1446 |
Sep | 2017 | 1123 |
Oct | 2017 | 986 |
Nov | 2017 | 964 |
Dec | 2017 | 1069 |
Jan | 2018 | 1125 |
Feb | 2018 | 940 |
Mar | 2018 | 1008 |
Apr | 2018 | 916 |
Downlod the Excel data of Monthly Sales for Office Supply and Stationery Stores and follow the steps below for regression based-time series forecasting. To be able to receive full credit, you must show your computations in the space provided for each question.
The Census Bureau tracks a variety of retail and service sales using the Monthly Retail Trade Survey. Consider the monthly sales (in millions of dollars) from January 2014 through April 2018 for office supply and stationery stores.
1. Create a time plot for monthly sales for office supply and stationary stores with the months labeled 1 for January, 2 for February, and so on. Show your plot in the space provided below:
(2p.)
2. Interpret the characteristics of monthly sales for this sector in terms of time series component, such as trend, seasonality, cyclical pattern etc. over the time. Do you observe any pattern from the data that repeats itself at a regular interval?
(4p.)
3. In which month do you observe a dramatic increase or decrease for the sales? Explain the reason very briefly.
(2p.)
4. Regress the monthly sales to a time variable and show the regression output in the space provided below. Interpret the results in terms of explained variability and the significance of the model.
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