1. Pie Sales

4. Start with a question. Are pie sales increasing? What day of the week has the biggest sales? What day of the week do they sell the least number of pies?

5. Draw an appropriate graph of your data.

6. This type of graph is called a time series graph.

7. Draw in the trendline.

8. Describe the short-term and long-term features of your data as they are shown by your graph. Describe at least 2 of the most important features and be specific about what they are and when they occur. The features you should be looking for are things like: What day of the week has the highest number of pies sold? Was there an unusual value that was different from the others (an extreme value)? Are pie sales increasing or decreasing over time or stable- what could be influencing your trendline?

9. Describe the short-term and long-term features of your data as they are shown by your graph. Describe at least 2 of the most important features and be specific about what they are and when they occur. What day of the week has the highest number of pies sold? Monday Was there an unusual value that was different from the others (an extreme value)? Wednesday in week 4 was very low Are pie sales increasing or decreasing over time or stable- what could be influencing your trendline? Increasing but the Wednesday makes it look as though they are decreasing. The overall trendline indicates a decrease because it has a negative gradient.

11. Why do I think the number of pies sold is increasing? Let’s look at Monday’s sales

12. Why do I think the number of pies sold is increasing? Let’s look at Tuesday’s sales

13. Why do I think the number of pies sold is increasing? Let’s look at Wednesday’s sales Outlier

14. Why do I think the number of pies sold is increasing? Look at Thursday’s sales

15. Why do I think the number of pies sold is increasing? Look at Friday’s sales

16. Why do I think the number of pies sold is increasing? It obviously depends on which day of the week you are talking about.

17. Use your graph to predict a future value or a previous value of your time series. Let’s try and predict the sales for the following Monday

18. Use your graph to predict a future value or a previous value of your time series. About 110

19. What could explain the very low Wednesday sales value.

20. We don’t have any information but could speculate that maybe the shop closed early or opened late. Maybe they ran out of pies to sell.