Reference no: EM131939482

You may work with at most two other students in the class. You must include the names of the students you worked with at the beginning of your report. Your homework must be submitted to Canvas as a Zip file (extension .zip, no other extension allowed NO .tar, NO .7z) with the title HW3_FirstNameLastName.zip and must consist of the following:

- A report in Word answering the questions (but without the code). If the questions ask for graphs, it should also include the graphs you generated in R as inserted images or screenshots.
- Source files in R as well as the original CSV data files.

- Please also include your name in all the files you submit, either in the titles, at the top of the Word document or as comment in the R file.

Problem 1 (CART)

Analytics EdgeLetter Recognition exercise (starting p.409),all questions.

Problem 2 (Clustering)
Analytics Edge Document Clustering exercise (starting p.415), all questions, including c) (it will not be extra credit for our assignment!)

Problem 3 (Real-life applications)

1. Make a summary in Word of at least 400 words and not more than 800 words of the paper "Analyzing user preferences using Facebook fan pages" posted on Canvas, explaining the clustering method used and describing the resulting clusters. Don't read the appendix. (Note: SPSS is a statistical software like R, except that it is not open-source).

2. Make a summary in Word of at least 500 words of Chapter 14 of the Analytics Edge textbook, making sure to include a brief description of each section, take particular care to describe the clustering approach in 14.3 Defining Peer Groups (among other things) and the Condorcet clustering method (except the "optimal clustering" section, which is starred and is therefore more advanced than the other sections) and answer the question: how can analytics be used to detect Medicaid fraud?

Attachment:- Assignment.rar