This 4 page paper uses data supplied by the student to answer three questions. The first demonstrates the way in which three point averages and five point averages may be calculated, uses the case study provided. The second question presents the results of the data and the moving average results in graphic format along with the inclusion of a trend line. The last question considers which of the two moving averages is best. The bibliography cites 1 source.
Name of Research Paper File: TS14_TE35point.doc
Unformatted Sample Text from the Research Paper:
geraniums. When looking at forecasting it is useful to be able to identify trends and then use trends in order to project the potential future demand. The benefit of using
a point moving average is seen in the way that the data is smoothed which allows a graph to be drawn with a line that has the best fit to
the data. The line may then be used to forecast future demand. Using the data we can calculate the three point moving
averages and use this to make a forecast. To calculate a three point average there will be the use of three data points for each day, the data is taken
from the day before, the day being calculated and the next day and averaged; the day for which the average being calculated in usually the middle data point. So we
cannot calculate this for day one, as there is no data for the day before. To calculate the moving average for day two we take the data from days 1,
2 and 3 and then divide it by 3. This is then repeated, so the three point average for day three takes the demand data from days 2, 3 and
4 and divides by 3. This is repeated for all the days (except the last day as there are not three data point which can be used. The results for
this are shown in table 1. The smoothed data will then be used to create a forecast, which we assume to be for day 15, using the data, which
gives a demand of 164. However, the value is also in the way that the smoothing will help to display and trends. The data shown in table 1 is