DIGIT 410: Data Visualization

Textbook Information

All required materials are provided in the course. 

Published Remarks

None

Hardware Requirements

This course contains audio/video content, and computer audio capabilities are recommended. However, transcripts and/or captioning are provided.

Software Requirements

Microsoft Excel is required and is provided by the University. Students may optionally use Jupyter Notebooks, a free and open-source program that may be downloaded or used in the cloud. Instructions for accessing Excel and Jupyter Notebooks are provided in the course.

Proctored Exams

None

Course Description

Method of Course Delivery: Remote Asynchronous (RA) [Class meets remotely. 100% of the class will be taught remotely asynchronously.]

In-depth understanding of techniques and software for data visualization. Students will be introduced to complex data sets and learn how to present findings in interactive and innovative ways.

By the conclusion of this course, you will be able to take a set of behavioral data (numbers that measure human behavior) and create an informative visualization of this data. The Data Visualization course is an introduction to the techniques and software for the creation of visual data representation. Students will learn how to effectively communicate information through graphical interpretations using both static/basic designs.

Course Pre-requisite(s): PSYCH 200 or STAT 200

Credits: 3

Learning Objectives

By the end of this course, successful students will be able to:

  • Apply the fundamental principles of data visualization. This requires an understanding of the different types of data visualizations, the elements of effective data visualization, and the principles of good design.
  • Select the appropriate data visualization for a given task. This involves considering the type of data, the audience, and the desired outcome.
  • Create effective data visualizations using a variety of tools.
  • Evaluate the effectiveness of data visualizations. This involves considering factors such as clarity, accuracy, and persuasiveness.
  • Communicate the results of data visualizations effectively through storytelling. This includes being able to explain the findings of a data visualization to a variety of audiences in a way that they can understand.

Course Structure

All course activities are contained in modules, where you will find:

  • An overview page, which serves as your guide to the module
  • Lesson materials and resource pages
  • Activities and assessments

This course consists of 15 content modules. 

Course Assessments

This course contains the following graded assessments.

  • Reading Worksheets: Reading worksheets are open-note, open-book quizzes over assigned course textbook readings. This course contains 13 reading worksheets/quizzes worth 20 points each and consists of 20 multiple-choice questions randomly drawn from a question bank. Therefore, worksheet/quiz content will vary for each learner. You may complete them while you read or after you read. Each quiz may be submitted only once. 
  • Assignments: Assignments in this course give you the opportunity to practice the tools and concepts of data visualization. This course contains 12 assignments worth 10 points each. 
  • Discussions: Discussions provide an opportunity to evaluate data visualization processes and course progress. This course contains 13 discussions worth 10 points each.
  • Projects: Projects are substantial assignments that synthesize learning in the course. This course contains 3 projects worth 50 points each. 

Completing assignments on a phone or tablet is not recommended. Please make backup copies of your work. There is only one certainty in electronic devices: they crash and lose documents at the most important times. Don’t give it a chance.

Course Grading

The final course grade is determined as follows:

Assessment Categories and Grade Calculation
Assessment Points Percentage of Final Grade
Reading Worksheets (13 at 20 points each) 260 20%
Assignments (12 at 10 points each) 120 20%
Discussions (13 at 10 points each) 130 20%
Projects (3 at 50 points each) 150 40%
TOTAL 660 100%

Letter grades will be based on the following scale:

Grading Scale
Letter Grade Range
A ≥ 93.00%
A- 90.00 – 92.99%
B+ 87.00 – 89.99%
B 83.00 – 86.99%
B- 80.00 – 82.99%
C+ 77.00 – 79.99%
C 70.00 – 76.99%
D 60.00 – 69.99%
F ≤ 59.99%