Case Study 1: Forecasting

Due Week 5 and worth 75 points

Using the Northern College Health Services visit volume in Appendix 6-1 on page 113 of the textbook, for this assignment, you will be providing a forecast of the number of clinic visits for November 2008 using the average change, confidence interval, average percent change, moving averages, and exponential smoothing forecasting methods. Use the Internet or Strayer Library to research at least two (2) examples of the forecasting methods being used in health services organizations.

Write a two to three (2-3) page paper in which you:

1. Explain each step in the forecasting process for each method.
2. Provide a brief summary of your researched health services organizations implementing the forecasting methods.
3. Provide a forecast of the number of clinic visits for November 2008 using each method of the forecasting process.
4. Conclude which forecasting method provides the best forecast, and provide a rationale for your conclusion.

Your assignment must follow these formatting requirements:

• Be typed, double spaced, using Times New Roman font (size 12), with one-inch margins on all sides; citations and references must follow APA or school-specific format. Check with your professor for any additional instructions.
• Include a cover page containing the title of the assignment, the student’s name, the professor’s name, the course title, and the date. The cover page and the reference page are not included in the required assignment page length.

The specific course learning outcomes associated with this assignment are:

• Evaluate forecasting strategies and methods.
• Use technology and information resources to research issues in quantitative methods for health services.
• Write clearly and concisely about quantitative methods for health services using proper writing mechanics.

 I have a mini-follow up, I will pay for this. Wondering if you could do this (shouldn’t take long) and it is using the former assignment below. 

“When you use a Python distribution like Canopy or Anaconda, you’ll sometimes (or often) find that a package you want to use isn’t included in it by default.  There are various ways of installing additional packages. They vary depending on the distribution you are using.

Let’s install something new.  The Python package pandas-profiling provides a means of summarizing the data in a Pandas DataFrame.  As you may know by now, Pandas DataFrames are a workhorse for manipulating and managing data for scientific and other uses.  

Find pandas-profiling online (Hint: Gitbub).   Then, install it in the Python distribution.  Give pandas-profiling a try using the assignment data.   Explain what you did and include code where necessary.  Don’t forget TAT.”