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Interactive Data Visualization

Home » Accreditation » ACE Credit » Interactive Data Visualization

Interactive Data Visualization

This course will teach you the principles of the visual display of data both for presentation and analysis data.

This course will teach you the principles of the visual display of data both for presentation and analysis data.

$589 | Enroll Now
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  • Overview
  • Learning Outcomes
  • Instructors
  • Syllabus
  • Dates
  • Prerequisites
  • Student Stories
  • FAQS
  • Requirements
Menu
  • Overview
  • Learning Outcomes
  • Instructors
  • Syllabus
  • Dates
  • Prerequisites
  • Student Stories
  • FAQS
  • Requirements

Overview

In this course you will learn about the interactive exploration of data, and how it is achieved using state-of-the-art data visualization software. You will learn to explore a range of different data types and structures, and about various interactive techniques for manipulating and examining data to produce effective visualizations. The learning process is hands-on as students are guided through an analysis of quantitative business data to discern meaningful patterns, trends, relationships, and exceptions that reveal business performance, potential problems and opportunities.

Learning Outcomes

Students who complete this course will be able to:

  • Apply principles of perception to data visualization
  • Use software tools to interactively visualize relationships among variables
  • Analyze distributions of data visually
  • Use a range of displays to explore data
  • Use parallel coordinate plots, scatterplots, and trellising to analyze multivariate data
  • Visualize hierarchical data with treemap

Who Should Take This Course

Statistical analysts and data miners who need to explore and graph multivariate data, either to form impressions of the data or as a preliminary step to performing statistical tests or building models.

Instructors

dr-adil-yalcin

Dr. Adil Yalcin

Adil Yalcin is the founder and CEO of Keshif. His work is at the intersection of analytics, design, engineering, and business development. He completed his Ph.D. in Computer Science at the University of Maryland as a member of the Human-Computer Interaction Lab. In his research, he created the basis of Keshif as the next-generation data exploration platform. His passion is providing refined, effective, principled solutions that lower barriers of complex tools and complex processes, i.e. solutions that are, in Einstein's words, as simple as possible, but not simpler. His academic work in data visualization and analysis has been published and cited in various books, proceedings, and academi...

See Instructor Bio

Course Syllabus

Week 1

  • Information visualization characterization and history
  • Elements of visual perception
  • Software introduction and data preparation (merging data, getting started, export)

Week 2

  • Interaction techniques
  • Distribution analysis
  • Hands-on visual exploration of business data

Week 3

  • Time Series
  • Multivariate views (scatterplots, parallel coordinate plots, trellising)
  • Treemaps for hierarchical data

Week 4

  • Specialized visualizations
  • Video demonstrations of novel techniques
  • From visualization to visual analytics

Class Dates

2021

Mar 12, 2021 to Apr 9, 2021

Jul 9, 2021 to Aug 6, 2021

Nov 12, 2021 to Dec 10, 2019

2022

No classes scheduled at this time.

2023

No classes scheduled at this time.

Send me reminder for next class

Prerequisites

Introductory Statistics

We assume you are versed in statistics or have the equivalent understanding of topics covered in our Statistics 1 and Statistics 2 courses. but do not require them as eligibility to enroll in this course. Please review the course description for each of our introductory statistics courses, estimate which best matches your level of understanding of the material covered in these courses, then take the short assessment test for that course. If you can not answer more than half of the questions correctly, we suggest you take our Statistics 1 and Statistics 2 courses prior to taking this course.

    • For Statistics 1 – Probability and Study Design, take this assessment test.
    • For Statistics 2 – Inference and Association, take this assessment test.

Frequently Asked Questions

Can I transfer or withdraw from a course?

We have a flexible transfer and withdrawal policy that recognizes circumstances may arise to prevent you from taking a course as planned. You may transfer or withdraw from a course under certain conditions.

  • Students are entitled to a full refund if a course they are registered for is canceled.
  • You can transfer your tuition to another course at any time prior to the course start date or the drop date, however a transfer is not permitted after the drop date.
  • Withdrawals on or after the first day of class are entitled to a percentage refund of tuition.

Please see this page for more information.

Who are the instructors at the Institute?

The Institute has more than 60 instructors who are recruited based on their expertise in various areas in statistics. Our faculty members are:

  • Authors of well-regarded texts in their area;
  • Advisory board members;
  • Senior faculty; and
  • Educators who have made important contributions to the field of statistics or online education in statistics.

The majority of our instructors have more than five years of teaching experience online at the Institute.

Please visit our faculty page for more information on each instructor at The Institute for Statistics Education.

Please see our knowledge center for more information.

What type of courses does the Institute offer?

The Institute offers approximately 80 courses each year. Topics include basic survey courses for novices, a full sequence of introductory statistics courses, bridge courses to more advanced topics. Our courses cover a range of topics including biostatistics, research statistics, data mining, business analytics, survey statistics, and environmental statistics.

Please see our course search or knowledge center for more information.

Do your courses have for-credit options?

Our courses have several for-credit options:

  • Continuing education units (CEU)
  • College credit through The American Council on Education (ACE CREDIT)
  • Course credits that are transferable to the INFORMS Certified Analytics Professional (CAP®)

Please see our knowledge center for more information.

Is the Institute for Statistics Education certified?

The Institute for Statistics Education is certified to operate by the State Council of Higher Education for Virginia (SCHEV). For more information visit: http://www.schev.edu

Please see our knowledge center for more information.

Visit our knowledge base and learn more.

FAQs + Knowledge Base

Related Courses

Visualization in R with ggplot2

This course will teach you ggplot as an implementation of the grammar of graphics in R. ggplot combines the advantages of base and lattice graphics while maintaining the ability to build up a plot step by step from multiple data sources.
Topic: Data Science, Using R | Skill: Intermediate | Credit Options: CAP, CEU

Additional Course Information

Organization of Course

This course takes place online at The Institute for 4 weeks. During each course week, you participate at times of your own choosing – there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.

At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.

Time Requirements

This is a 4-week course requiring 10-15 hours per week of review and study, at times of your choosing.

Homework

Homework in this course consists of guided exercises using state of the art software.

In addition to assigned readings, this course also has an end of course data modeling project, and example software files.

Course Text

The required text for this course is Now You See It: Simple Visualization Techniques for Quantitative Analysis by Stephen Few.  Note: This text is not available in digital format. For those residing outside the US and not able to purchase this text, you may use The Truthful Art by Albert Cairo instead.

Please order a copy of your course textbook prior to course start date.

Software

The use of Tableau software is illustrated and access to this program will be provided in the first lesson. Prior experience with Tableau is not expected or required.

Some students also use Spotfire, but it is not available as part of the course.  Want to use R?  Please see   our course: Visualization in R with ggplot2.

Software Uses and Descriptions | Available Free Versions
To learn more about the software used in this course, or how to obtain free versions of software used in our courses, please read our knowledge base article “What software is used in courses?” 

Course Fee & Information

Enrollment
Courses may fill up at any time and registrations are processed in the order in which they are received. Your registration will be confirmed for the first available course date unless you specify otherwise.

Transfers and Withdrawals
We have flexible policies to transfer to another course or withdraw if necessary.

Group Rates
Contact us to get information on group rates.

Discounts
Academic affiliation?  In most courses you are eligible for a discount at checkout.

New to Statistics.com?  Click here for a special introductory discount code.  

Invoice or Purchase Order
Add $50 service fee if you require a prior invoice, or if you need to submit a purchase order or voucher, pay by wire transfer or EFT, or refund and reprocess a prior payment.

Options for Credit and Recognition

This course is eligible for the following credit and recognition options:

No Credit
You may take this course without pursuing credit or a record of completion.

Mastery or Certificate Program Credit
If you are enrolled in mastery or certificate program that requires demonstration of proficiency in this subject, your course work may be assessed for a grade.

CEUs and Proof of Completion
If you require a “Record of Course Completion” along with professional development credit in the form of Continuing Education Units (CEU’s), upon successfully completing the course, CEU’s and a record of course completion will be issued by The Institute upon your request.

INFORMS-CAP
This course is recognized by the Institute for Operations Research and the Management Sciences (INFORMS) as helpful preparation for the Certified Analytics Professional (CAP®) exam and can help CAP® analysts accrue Professional Development Units to maintain their certification.

ACE CREDIT | College Credit
This course has been evaluated by the American Council on Education (ACE) and is recommended for the the upper division baccalaureate degree, 3 semester hours in data mining, statistics, or computer science. Please note that the decision to accept specific credit recommendations is up to the academic institution accepting the credit.

ACE Digital Badge
Courses evaluated by the American Council on Education (ACE) have a digital badge available for successful completion of the course.

Supplemental Information

There is no supplemental content for this course.

Miscellaneous

There is no additional information for this course.

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Interactive Data Visualization
$589 | Enroll Now
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