1. Make 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:

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?

3. In which month do you observe a dramatic increase or decrease for the sales? Explain the reason very briefly.

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.

5. Create indicator variables to represent each month as a category. Consider December data as a baseline model. How many indicator variables do we need to recode months as different categories?

6. Explain very briefly the reason why we need indicator variables, in other words why we need to recode each month as a different category and include in the regression analysis?

7. Regress the monthly sales to a time variable along with all indicator variables. The new model captures the linear trend along with the seasonal pattern in the time series. Show the output of the trend-and-season model and the multiple regression equation including all indicator variables in the space provided below. Interpret the results in terms of model fit which is reflected in explained variability and the significance of the trend-and-season model.

8. Compare and contrast the model fits of trend-only model and trend-and-season model in terms of explained variability and the significance of the model.

9. Test the significance of each indicator variable and report if there is any insignificant variable exists in the trend-and-season model.

10. Explain very briefly the reason why some coefficients of the indicator variables are negative from trend-and-season model.

11. Report the indicator variable that shows the highest coefficient in the trend-and-season model and explain very briefly why one of the coefficients is quite high relative to other coefficients of indicator variables.

12. What are the predicted monthly sales for the month of August using the trend-and-season model? Explain the results very briefly.

A B C Month Year Sales Jan 2014 1489 W N Feb 2014 1292 Mar 2014 1351 Apr 2014 1263 May 2014 1205 Jun 2014 1093 8 Jul 2014 1255 Aug 2014 1699 10 Sep 2014 1392 11 Oct 2014 1248 12 Nov 2014 1163 13 Dec 2014 1389 14 Jan 2015 1432 15 Feb 2015 1221 16 Mar 2015 1194 17 Apr 2015 1163 18 May 2015 1103 19 Jun 2015 1056 20 Jul 2015 1160 21 Aug 2015 1586 22 Sep 2015 1314 23 Oct 2015 1148 24 Nov 2015 1073 25 Dec 2015 1285 26 Jan 2016 1247 27 Feb 2016 1136 28 Mar 2016 1171 29 Apr 2016 1099 30 May 2016 1060 31 Jun 2016 982 32 Jul 2016 1026 33 Aug 2016 1544 34 Sep 2016 1251 35 Oct 2016 1032 36 Nov 2016 1007 37 Dec 2016 1169 38 Jan 2017 1228 39 Feb 2017 1004 40 Mar 2017 1096 41 Apr 2017 953 42 May 2017 996 43 Jun 2017 930 44 Jul 2017 962 45 Aug 2017 1446 46 Sep 2017 1123 47 Oct 2017 986 48 Nov 2017 964 49 Dec 2017 1069 50 Jan 2018 1125 51 Feb 2018 940 52 Mar 2018 1008 53 Apr 2018 916 54 55 56 57 58