Forecasting Hsm 260
Forecasting
HSM 260
07/19/2013
Forecasting
Exercise 9.1
In the text, exercise 9.1 provides data for Palmdale Human Services. In this exercise it asks for the 20X5 figures using several forecasting models. The process of find 20X5 will include the use of moving averages, weighted moving averages, and exponential smoothing. The Palmdale Human Services personal expenses for the past four years are represented in the following data: Fiscal Year | Expense | 20X1 | $5,250,000 | 20X2 | $5,500,000 | 20X3 | $6,000,000 | 20X4 | $6,750,000 |
For moving averages and weighted moving averages, use only the data for the past three fiscal years: Moving Averages Fiscal Year | Expenses | 20X2 | $5,500,000 | 20X3 | $6,000,000 | 20X4 | $6,750,000 | 20X5 | $6,083,000 |
20X2-4 $18,250,000
$18,250,000/3(divide) = $6,083,000 (20X5)
Weight averages Fiscal Year | Expense | Value | 20X2 | $5,500,000 | 1=$5,500,000 | 20X3 | $6,000,000 | 2=12,000,000 | 20X4 | $6,750,000 | 3=$20,250,00 | 20X5 | $6,300,000 | 6=$37,750,000 |
20X5 $37,750,000 divided by 6 (totaled values1+2+3 =6) = $6,291,667 or $6,300,000 weighted average
Exponential Smoothing
Based on the information collected we can generate a new forecast. I believe the alpha method of 0.9 is the method that will be used for it has the latest information. The formula would look like this: NF = LF + α (LD – LF).
Last Forecast (LF) = $6,300,000
Last Data (LD) = $6,750,000α = 0.9
Exercise 9.3
This exercise is asking to find the forecast from all sources (total revenues); the following data represent this information.
Palmdale’s past four fiscal years: Fiscal Year | Total Revenues | 20X1 | $15,000,000 | 20X2 | $14,250,000 | 20X3 | $14,000,000 | 20X4 | $13,500,000 |
Forecasting the total revenues for fiscal year 20X5 I will use the moving averages, weighted moving averages, exponential smoothing, and time series regression.
Moving Averages Fiscal Year | Total Revenues
HSM 260
07/19/2013
Forecasting
Exercise 9.1
In the text, exercise 9.1 provides data for Palmdale Human Services. In this exercise it asks for the 20X5 figures using several forecasting models. The process of find 20X5 will include the use of moving averages, weighted moving averages, and exponential smoothing. The Palmdale Human Services personal expenses for the past four years are represented in the following data: Fiscal Year | Expense | 20X1 | $5,250,000 | 20X2 | $5,500,000 | 20X3 | $6,000,000 | 20X4 | $6,750,000 |
For moving averages and weighted moving averages, use only the data for the past three fiscal years: Moving Averages Fiscal Year | Expenses | 20X2 | $5,500,000 | 20X3 | $6,000,000 | 20X4 | $6,750,000 | 20X5 | $6,083,000 |
20X2-4 $18,250,000
$18,250,000/3(divide) = $6,083,000 (20X5)
Weight averages Fiscal Year | Expense | Value | 20X2 | $5,500,000 | 1=$5,500,000 | 20X3 | $6,000,000 | 2=12,000,000 | 20X4 | $6,750,000 | 3=$20,250,00 | 20X5 | $6,300,000 | 6=$37,750,000 |
20X5 $37,750,000 divided by 6 (totaled values1+2+3 =6) = $6,291,667 or $6,300,000 weighted average
Exponential Smoothing
Based on the information collected we can generate a new forecast. I believe the alpha method of 0.9 is the method that will be used for it has the latest information. The formula would look like this: NF = LF + α (LD – LF).
Last Forecast (LF) = $6,300,000
Last Data (LD) = $6,750,000α = 0.9
Exercise 9.3
This exercise is asking to find the forecast from all sources (total revenues); the following data represent this information.
Palmdale’s past four fiscal years: Fiscal Year | Total Revenues | 20X1 | $15,000,000 | 20X2 | $14,250,000 | 20X3 | $14,000,000 | 20X4 | $13,500,000 |
Forecasting the total revenues for fiscal year 20X5 I will use the moving averages, weighted moving averages, exponential smoothing, and time series regression.
Moving Averages Fiscal Year | Total Revenues