代写Operations Analytics、代做Python程序设计

Operations Analytics
Homework 4 Total: 10 points
Due Date: Thursday, April 4th by start of class on Canvas. 
No late assignment will be accepted. 

Chinese Pharmaceutical Case 

The purpose of the assignment is to provide an exercise in using time series forecasting methods. 

The file “CP.xlsx” on Canvas contains the data from the case.  

Make sure to explain your process for constructing each forecast as well as provide the Spreadsheet/Python code with your work. Complete the table on the next page summarizing your findings. 

1.(1 points) Construct the Exponential Smoothing forecast discussed in the case, assuming initial forecast for Aug 2009 of 3,303 (the July 2009 data). 

2.(1 point) Recommend an exponential smoothing parameter  which minimizes MAD (mean absolute deviation) on the three years of data. 

3.(4 points) Choose Static (DTDS+ES) or Recursive (Winter’s) forecasting method and set the corresponding parameter values to minimize MAD on the three years of data. 

4.(1 point) Provide a distributional forecast for sales in July 2012.

5.(1 point) Provide another distributional forecast for sales in Jan 2013.

Management receives the data for the following 12 months in the “CP_testing.xlsx” spreadsheet.

6.(2 points) Use this new data as the “testing set” to validate your forecasting method. Fill in the table below:

Forecasting Method Chosen    Recommended parameter values    July 2012 distributional forecast    Jan 2013 distributional forecast    MAD 
“test” set
DTDS+ES
Or Winter’s                

If homework is completed in a team of less than four members and would like information about the point allocations per question, please contact the instructor.

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