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Course Description
This course introduces students to the core areas of diagnostic analytics. The diagnostic analysis takes descriptive data a step further by examining the relationships between variables through root cause analysis. Students will learn current tools and techniques, including external environmental factors, that allow analysts to explain why the patterns are observed in data and discover relationships between two or more attributes of the data. Students will have the opportunity to review case studies and work on real-world projects throughout the course.
This course introduces students to the core areas of diagnostic analytics. The diagnostic analysis takes descriptive data a step further by examining the relationships between variables through root cause analysis. Students will learn current tools and techniques, including external environmental factors, that allow analysts to explain why the patterns are observed in data and discover relationships between two or more attributes of the data. Students will have the opportunity to review case studies and work on real-world projects throughout the course. (3 credits)
Prerequisite: DA 201W
Objectives
Upon completion of this course, you should be able to
- Combine multiple data sets in order to better apply diagnostic analytics
- Implement appropriate correlation methods to establish relationships among variables in data
- Analyze spatial data for patterns that explain connections in data
- Implement multivariable techniques to establish relationships in data
- Create visualizations that effectively communicate diagnostic analytics
- Create interactive visualizations to aid in performing diagnostic analytics
- Develop effective teamwork and communication skills
Course Assignments
The course contains the following graded assignments in the following categories:
- Assignments and Activities: This course contains twelve (12) assignments that require use of various course software tools. For assignments, you may be copying and pasting code and/or output from these tools into Word documents for upload. You may use your notes or course materials for assignments and for the activity. These assignments should be completed individually. Points possible for individual assignments range from 15 to 30. See the assignment descriptions in Canvas for more information, including how each will be assessed.
- Estimation Challenges (Discussions): This course contains a total of six (6) Estimation Challenges. These are set up as discussion boards. You will not be able to see your peers’ responses until after you make your initial post. These are meant to develop an important critical thinking skill – your ability to reason and estimate quantities. Note that these Estimation Challenges discussions require an initial post and at least 2 response posts to classmates. Initial posts are due on Thursdays in the weeks they are assigned, with follow-up posts due on or before the end of the same week. Discussions are graded according to your estimation explanation and critical analysis. While these challenges could have a definitive answer, your reasoning for how you reached your answer is what is most important. See the Estimation Challenges grading rubric on the information page in the Orientation page or at each Estimation Challenge discussion board (in the “Show More” menu) for details.
- Final Exam: There is a final exam at the end of the course consisting of questions from all of the course content. You will find practice quizzes throughout the course and in a review module to help you to prepare for the exam.
- Final Project: There is a final project during the latter half of the course. The final project is split up into four phases. You will work in a small group to complete these assignments. Collaboration with others is an important skill to develop. The details of each phase of the final project can be reviewed in the module titled Final Project Overview and Information.