Forcasting Indices

Forecasting is a method that businesses use to predict what future values may be. All forecasting methods can be divided into two broad categories: qualitative and quantitative. Many forecasting techniques use past or historical data in the form of time series. A time series is simply a set of observations measured at successive points in time or over successive periods of time. Forecasts essentially provide future values of the time series on a specific variable such as sales volume. Division of forecasting methods into qualitative and quantitative categories is based on the availability of historical time series data. Qualitative forecasting is most useful when past data is unkown and quanititative forecasting is most useful when past data is known (Advameg, Inc., 2011). The following winter historical inventory data from the University of Phoenix OLS was used to determine the index and forecast with indices.

Typical Seasonal Demand for Winter Highs

Actual Demands (in units)

Month Year 1 Year 2 Year 3 Year 4

1 55,200 39,800 32,180 62,300

2 57,350 64,100 38,600 66,500

3 15,400 47,600 25,020 31,400

4 27,700 43,050 51,300 36,500

5 21,400 39,300 31,790 16,800

6 17,100 10,300 31,100 18,900

7 18,000 45,100 59,800 35,500

8 19,800 46,530 30,740 51,250

9 15,700 22,100 47,800 34,400

10 53,600 41,350 73,890 68,000

11 83,200 46,000 60,200 68,100

12 72,900 41,800 55,200 61,100

The average for each year is calculated by adding each value in that year and dividing by 12. For example, year 1 would include 55,200 + 57,350 + 15,400, etc/ 12. The following chart includes the averages as calculated in excel.

Year 1 Year 2 Year 3 Year 4

Averages 38112.5 40585.83 44801.67 45895.83

After the averages were calculated, then the averages were used to calculate the indices. Index numbers characterize the magnitude of economic changes over time. They can describe trends in a change of any economic data....