Details:
Access the “Entrepreneurship and the U.S. Economy”
page of the Bureau of Labor Statistics website (https://www.bls.gov/bdm/entrepreneurship/entrepreneurship.htm)
and complete this forecasting assignment according to the directions provided
in the “Forecasting Case Study: New Business Planning” resource.
Use an Excel spreadsheet file for the calculations and
explanations. Cells should contain the formulas (if a formula was used to
calculate the entry in that cell). Students are highly encouraged to use the
Excel resource, “Forecasting Template,” to complete this assignment.
Mac users can use StatPlus:mac LE, free of charge, from
AnalystSoft.
Prepare the assignment according to the guidelines found in
the APA Style Guide, located in the Student Success Center. An abstract is not
required.
Case Study: New Business Planning
Important
Note: Students must access the “Entrepreneurship and the U.S. Economy” page of
the Bureau of Labor Statistics websitein order to completethis
assignment.
Scenario
The generation of new business
start-up is vital to the growth of the economy as it builds new jobs and
creates new opportunities for the community. The Bureau of Labor Statistics
tracks new business development and jobs created on the website for the United
States Department of Labor. You have been tasked with forecasting economic
growth and decline patterns for new businessesin the United States.
Forecasting
Access the “Entrepreneurship and the
U.S. Economy” page of the Bureau of Labor Statistics website. Under the “Business
establishment age”heading, the first chart reviews new businesses less
than1year old during the March 1994to March 2015 period. Click on the [Chart data]
link below the chart:
Once the chart data window opens,
you will see the number of establishmentsthat are less than 1 year oldfor each
year during this period:
Using the five most recent years and
the “Forecasting Template” spreadsheet provided, complete the
forecasts for the next two periods and provide updated Totals and Average Bias,
median absolute deviation (MAD), mean squared error (MSE), and mean absolute
percentage error(MAPE) for all four charts. Provide a Summary Page in Excel
with a 500-750 word report on the analysis completed by the forecasting models.
Include review of error, recommendations on the best forecasting model to use,
and analysis of the business trend data for new business startup in the United
States.
|
Moving averages – 2 period moving average |
|||||||||||||
| Num pds | 3 |
|
||||||||||||
| Data | Forecasts and Error Analysis |
|||||||||||||
| Period | Demand | Forecast | Error | Absolute | Squared | Abs Pct Err | ||||||||
| Period 1 | 38 | |||||||||||||
| Period 2 | 40 | |||||||||||||
| Period 3 | 41 | 39 | 2 | 2 | 4 | 04.88% | ||||||||
| Period 4 | 37 | 40.5 | -3.5 | 3.5 | 12.25 | 09.46% | ||||||||
| Period 5 | 45 | 39 | 6 | 6 | 36 | 13.33% | ||||||||
| Total | 4.5 | 11.5 | 52.25 | 27.67% | ||||||||||
| Average | 1.5 | 3.833333 | 17.41667 | 09.22% | before forecast | |||||||||
| Bias | MAD | MSE | MAPE | |||||||||||
| Period 6 | 50 | 47.5 | 2.5 | 2.5 | 6.25 | 05.00% | ||||||||
| Period 7 | 44 | Average | after forecast period 6 | |||||||||||
| Bias | MAD | MSE | MAPE | |||||||||||
|
Moving averages – 3 period moving average | |||||||||||||
| Num pds | 3 |
|
||||||||||||
| Data | Forecasts and Error Analysis |
|||||||||||||
| Period | Demand | Forecast | Error | Absolute | Squared | Abs Pct Err | ||||||||
| Period 1 | 38 | |||||||||||||
| Period 2 | 40 | |||||||||||||
| Period 3 | 41 | |||||||||||||
| Period 4 | 37 | 39.66667 | -2.66667 | 2.666667 | 7.111111 | 07.21% | ||||||||
| Period 5 | 45 | 39.33333 | 5.666667 | 5.666667 | 32.11111 | 12.59% | ||||||||
| Total | 3 | 8.333333 | 39.22222 | 19.80% | ||||||||||
| Average | 1.5 | 4.166667 | 19.61111 | 09.90% | ||||||||||
| Bias | MAD | MSE | MAPE | |||||||||||
| Period 6 | 50 | 44 | 6 | 6 | 36 | 12.00% | ||||||||
| Period 7 | 44 | Average | after forecast period 6 | |||||||||||
| Bias | MAD | MSE | MAPE | |||||||||||
|
Exponential smoothing | |||||||||||||
| Alpha | 0.3 | |||||||||||||
| Data | Forecasts and Error Analysis |
|||||||||||||
| Period | Demand | Forecast | Error | Absolute | Squared | Abs Pct Err | ||||||||
| Period 1 | 38 | 38 | 0 | 0 | 0 | 0.00% | ||||||||
| Period 2 | 40 | 38 | 2 | 2 | 4 | 5.00% | ||||||||
| Period 3 | 41 | 38 | 3 | 3 | 9 | 7.32% | ||||||||
| Period 4 | 37 | 38 | -1 | 1 | 1 | 2.70% | ||||||||
| Period 5 | 45 | 38 | 7 | 7 | 49 | 15.56% | ||||||||
| Total | 11 | 13 | 63 | 30.58% | ||||||||||
| Average | 2.2 | 2.6 | 12.6 | 06.12% | Before forecast | |||||||||
| Bias | MAD | MSE | MAPE | |||||||||||
| SE | 4.582576 | |||||||||||||
| Period 6 | 50 | 38 | 12 | 12 | 144 | 24.00% | ||||||||
| Period 7 | 44 | Average | after forecast period 6 | |||||||||||
| Bias | MAD | MSE | MAPE | |||||||||||
