2. Data collected over a period of time

4. Example

5. Data seems pretty random!!

6. Some go up,

7. Data seems pretty random!! Some go up, some down

8. Data seems pretty random!! Some go up, some down What the?

9. Drawing a graph helps a bit

10. You can see the general trend

11. Looking closer you can see a cyclic nature to this data

12. Every third value is a low one

13. We want to be more specific about the general trend

14. We want to be more specific about the general trend, so we calculate a MOVING AVERAGE

15. Our data seems to occur in groups of three, so we will use a 3 POINT moving average

16. How does it work? Calculate the average of the first group of 3 points

17. 3. Calculate the average of the second 3 points 1. Drop the first Monday 2. Pick up the second Monday

18. 3. Calculate the average of the third group of 3 points 1. Drop the first Wednesday 2. Pick up the second Wednesday

19. 3. Calculate the average of the fourth group of 3 points 1. Drop the first Friday 2. Pick up the second Friday

20. Keep moving the averages down until you have run out of points to include

21. Remember… Every moving average needs to include one of each type of value, ie 1 x Monday 1 x Wednesday 1 x Friday in some order

22. Plotting this moving average on the original graph looks like this…

23. The moving average looks much more linear than the raw data and can be used more effectively as a regression basis

24. Using the Statistics Mode to calculate a linear regression for the moving average

25. 1. Using ONLY times that actually have moving averages, enter those time values into LIST 1

26. Using the Statistics Mode to calculate a linear regression for the moving average 1. Using ONLY times that actually have moving averages, enter those time values into LIST 1 2. Enter the moving averages into LIST 2

27. Using the Statistics Mode to calculate a linear regression for the moving average 1. Using ONLY times that actually have moving averages, enter those time values into LIST 1 2. Enter the moving averages into LIST 2 3. CALC – LINEAR REG

28. We now have a STRAIGHT line through the data,

29. We now have a STRAIGHT line through the data, and can use it to make predictions