Flexible, affordable statistics education.
Designed to help you master the software you need to enhance your skills and the practical experience you need to get ahead.
Designed to help you master the software you need to enhance your skills and the practical experience you need to get ahead.

Interactive Data Visualization
taught by Galit Shmueli or Catherine Plaisant
This course covers the principles of the visual display of data, both for presentation and analysis.
Instructor(s):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.
Dates: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. Please use this printed registration form, for these and other special orders.
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. Multiple course registrations may be entitled to tuition discounts; read more.
Interactive Data Visualization
taught by Galit Shmueli or Catherine Plaisant
This course is about the interactive exploration of data, and how it is achieved using state-of-the-art data visualization software. Participants will learn to explore a range of different data types and structures. They will learn about various interactive techniques for manipulating and examining the data and producing effective visualizations.
The course is very hands-on in terms of the learning process. Participants will be guided through an exploration of quantitative business data to discern meaningful patterns, trends, relationships, and exceptions that reveal business performance, potential problems and opportunities.
Prerequisite(s):If you are unclear as to whether you have mastered the requirements, try these placement tests here.
SESSION 1
HOMEWORK:
Homework in this course consists of guided exercises in writing code for producing graphs.
This course takes place over the internet 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.
The course typically requires 15 hours per week. 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.
The required text for this course is Now You See It: Simple Visualization Techniques for Quantitative Analysis by Stephen Few. It can be purchased on Amazon here. Please make sure you have the book prior to the beginning of the course.
Software:Participants will benefit from being able to implement illustrated techniques in a visualization package. The use of Spotfire is illustrated. For information on obtaining a trial package of Spotfire, click here.
MAC USER: you must check with the software manufacturer to be sure that the software/capabilities you are interested in are available for the Mac, before registering for this course.
Interactive Data Visualization
taught by Galit Shmueli or Catherine Plaisant
"I need to know R to perform my job as I am a product manager for a software company that interacts with R. I am now able to understand R scripts and hopefully contribute some of my own. The instructor's videos were great. Just hearing his voice made it more personal. This was my first ever web based course and I really enjoyed it although I had to work hard."