Data mining homework help

Data mining homework help

Week 3 – Discussion 2

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Your initial discussion thread is due on Day 3 (Thursday) and you have until Day 7 (Monday) to respond to your classmates. Your grade will reflect both the quality of your initial post and the depth of your responses.
Data   Mining

Health care data comes in many different forms. The data is collected, organized, and analyzed to improve patient outcomes and health care processes. Data mining is a technique that researchers use to look for hidden patterns and relationships in large amounts of data. In this discussion you will evaluate a large data set complied by the U.S. Department of Health & Human Services.  This data set contains breeches of protected health information affecting 500 or more individuals. Use the data set to address the following:

  • How many records are in this file?
  • What is the name of the covered entity in your State      that had the highest number of individuals affected (be sure to identify      your state and the name of the institution)?
  • What type of breech occurred?
  • Describe the type of violation.
  • How could this violation have been avoided?
  • How would you apply the data mining methods of      clustering and association rule mining to this file?

Guided response: Your initial post should be a minimum of 200-250 words.

  • Utilize a minimum of two scholarly sources, excluding      the textbook.
  • Sources should be cited in APA format, as outlined in      the Ashford Writing Center.
  • You must respond to at least two of your classmate’s      posts by Day 7.
  • Your three required posts must be on three different      days of the week.
  • In  reading the other initial posts, identify at      least two similarities regarding the cause of the violation.  In your      opinion, would the monetary penalty be significant to encourage policies      to avoid a re-occurrence of the violation?  Why or why not?

Carefully review the Grading Rubric for the criteria that will be used to evaluate your discussion.

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