MBI 664 Data Visualization and Visual Analytics

Course Description:

MBI 664 – Data Visualization and Analytics (3, 0, 3) Core concepts for the design, creation, and visualization of large volume of data. The student will first learn the concepts behind data visualization and R programming and then apply these concepts to analyze large scale data in a series of assigned applications and then do a self-initiated project of sufficient complexity to develop the skills necessary for large scale data analysis

Student Learning Objectives:

• Acquire abilities to address problems in data sourcing and integration of data from multiple sources.

• Understand the concepts behind summarizing and analyzing data.

• Learn the commonly accepted guidelines for a good visual presentation of data.

• Learn to present data with visual representations that allow your audience to see the unexpected.

• Develop abilities to parse and analyze data to support business decisions through exercises based on large datasets.

Textbooks:

·  The Functional Art: An Introduction to Information Graphics and Visualization [Paperback] Publisher: New Riders; First Edition (2012) ISBN-10: 0321834739 ISBN-13: 978-0321834737

·  R for Everyone: Paperback– (2013) by Jared Lander (Author) ISBN-13: 978-0321888037ISBN-10: 0321888030- Edition: 1st

·  Visualize This: The Flowing Data Guide to Design, Visualization, and Statistics [Paperback] By Nathan Yau Publisher: Wiley; 1 edition (2011) ISBN-10: 0470944889 ISBN-13: 978-0470944882

Additional Readings

·  Data!: Fast and Easy Visual Analysis with Tableau Software Paperback– November 11, 2013 by Dan Murray (Author) ISBN-13: 978-1118612040ISBN-10: 1118612043 Edition: 1st

Course Format:

The class material covered is both conceptual and practical. You should employ a learning strategy that best suits you. In all cases though, feel free to contact the instructor during office hours or make appointments to meet with the instructor if the posted office hours are not convenient for you. Please post any queries related to the course on the discussion board in Blackboard and look for answers posted by the instructor. Please resort to e-mails only if course-related questions are not answered in the discussion board or your questions/concerns are of personal nature. Assignments will be posted in Blackboard and submitted only through Blackboard.

Evaluative Criteria:

There will be six unannounced quizzes. No makeup will be given for these quizzes. The students MUST complete the quizzes in the allocated time. While Blackboard may permit you to proceed with quizzes after the allocated time, Blackboard also notifies instructors when the time expired. Any quiz exceeding the time limit will NOT be graded. The four best of a total of six quizzes will be used for final grading. Student must retain hard copies of all assignments for verification.

Quizzes: 25%

Assignments: 40%

Final Examination: 15%

Project & Presentation: 20 %

Tentative Course Schedule

Please note that

·  the schedule noted below is subject to change especially in the form additional readings and

·  it is the students responsibility to note the changes announced through the Blackboard site

·  in addition to the topics noted here, sometime will be devoted to covering the software tools such as Tableau 8. The following topics will be covered in the order mentioned. For weekly assignments and readings, please refer to the Blackboard.

LECTURE / Resource
Introduction – Why Visualize / AC Chapter 1 and Handout
Intro to R and R packages / JL Chapters 1-3
Forms and Functions: Visualization as a Technology / AC Chapter 2
The Beauty Paradox / AC Chapter 3
Reading Data into R Chapter 6
Tools to visualize data / Yau Chapter 1 & 2
The Complexity Challenge / AC Chapter 4
Visualizing for the Mind / AC Chapters 5, 6 & 7
Information Graphics / AC Chapters 8 & 9
Visualizing patterns over time / Yau Chapter 4
Visualizing proportions / Yau Chapter 5
Visualizing relationships / Yau Chapter 6
Spotting differences / Yau Chapter 7
Visualizing spatial relationships / Yau Chapter 8
Tree Maps / Handouts
Project and Presentations

Material from R will be covered throughout the course.