30 Dec Use an Excel spreadsheet
Forecasting Case Study: New Business Planning
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.
This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.
You are not required to submit this assignment to Turnitin.
Forecasting Case Study: New Business Planning
Important Note: Students must access the “Entrepreneurship and the U.S. Economy” page of the Bureau of Labor Statistics website in order to complete this 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 businesses in 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 than 1 year old during the March 1994 to March 2015 period. Click on the [Chart data] link below the chart:
Once the chart data window opens, you will see the number of establishments that are less than 1 year old for 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.
.png” alt=”Text box: enter the past demands in the data area”>
Forecasting
Moving averages – 2 period moving average
Num pds
3
.png”>
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
.png”>
.png” alt=”Text box: enter the past demands in the data area”>
Forecasting
Moving averages – 3 period moving average
Num pds
3
.png”>
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
.png”>
.png” alt=”Text box: enter alpha (between 0 and 1), enter the past demands in the shaded column then enter a starting forecast. if the starting forecast is not in the first period then delete the error analysis for all rows above the starting forecast.”>
Forecasting
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
38.6
2.4
2.4
5.76
5.85%
Period 4
37
39.32
-2.32
2.32
5.3824
6.27%
Period 5
45
38.624
6.376
6.376
40.65338
14.17%
Total
8.456
13.096
55.79578
31.29%
Average
1.6912
2.6192
11.15916
06.26%
Before forecast
Bias
MAD
MSE
MAPE
SE
4.312608
Period 6
50
40.5368
9.4632
9.4632
89.55215
18.93%
Period 7
44
Average
after forecast period 6
Bias
MAD
MSE
MAPE
.png”>
.png” alt=”Text box: enter alpha and beta (between 0 and 1), enter the past demands in the shaded column then enter a starting forecast. if the starting forecast is not in the first period then delete the error analysis for all rows above the starting forecast.”>
Forecasting
Trend adjusted exponential smoothing
Alpha
0.3
Beta
0.7
Data
Forecasts and Error Analysis
Period
Demand
Smoothed Forecast, Ft
Smoothed Trend, Tt
Forecast Including Trend, FITt
Error
Absolute
Squared
Abs Pct Err
Period 1
38
38
38
0
0
0
00.00%
Period 2
40
38
0
38
2
2
4
05.00%
Period 3
41
38.6
0.42
39.02
1.98
1.98
3.9204
04.83%
Period 4
37
39.614
0.8358
40.4498
-3.4498
3.4498
11.90112
09.32%
Period 5
45
39.41486
0.111342
39.5262
5.473798
5.4738
29.96246
0.12164
Next period
41.16834
1.26084
42.42918
Total
6.003998
12.9036
49.78398
31.32%
41.16834
Average
1.2008
2.58072
9.956797
06.26%
Bias
MAD
MSE
MAPE
SE
4.073655
Next period
42.05093
0.617811
42.66874
Total
After forecast
Average
Bias
MAD
MSE
MAPE
SE
0
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