[Please Note: The Essential Data Science for Business: Descriptive Analytics, Exploratory Data Analysis, and Data Visualization has already occurred.
Go to the News Story for this event to read about what happened., or...
Missed this Event? To gain access to the recording of this event along with links to supporting files and information, complete the Registration Option for "Post Session Access" on the right hand side of this webpage.]
The tutorials in this NISS series involve the Top 10 analytics approaches of the key topics that are used in business today! Students and faculty, these are perhaps the top ten most important and practical topics that may not be covered in your program of study. (Review the Overview Presentation about all 10 Sessions).
Descriptive Analytics, Exploratory Data Analysis, and Data Visualization
Overview
Data analysis today involves more facets than the traditional statistics curriculum covered even a few decades ago. Even simple descriptive summaries now include methods beyond the scope of the classical statistical estimators. Exploratory data analysis now incorporates many new methods not seen in Tukey's pioneering book of that name. And visualization nowadays depends on algorithms that weren't practical or didn't exist on the computers of even a decade ago. Furthermore, big data sets (many rows, many columns, many items, ...) present special problems for analysis and visualization. This workshop covers strategies that help reduce data sets to manageable proportions and models that are interpretable when applied to massive problems. It also covers graphic representations most suitable for exploring multivariate data.
Instructor
Lee Wilkinson (Chief Scientist at H2O, and Adjunct Professor of Computer Science at the University of Illinois at Chicago)
Goals
NISS is interested in sharing knowledge. To this end, these webinars have been geared to provide practical information that you can use tomorrow. Examples, projects and code sharing are a part of these sessions wherever possible.
Series Prerequisites
Participants require a working knowledge of probability distributions, statistical inference, statistical modeling and time series analysis as a prerequisite. Students who do not have this foundation or have not reviewed this material within the past couple of years will struggle with the concepts and methods that build on this foundation.
Registration
Select a registration/payment option above the 'Register for this Event' button ($35 for this Data Science Essentials tutorial session, $250 for all 10 Essential Data Science for Business tutorial sessions. Can attend this live session? Post Session Access to tutorial materials and recording can be obtained for $35 after the event is over.). NISS Affiliates, (https://www.niss.org/affiliates-list), please send an email to officeadmin@niss.org.). Notifications: You will recieve an email that comes immediately to let you know you paid. Links to the event will come via email the day before and one hour prior to the actual session.
Agenda
About the Instructor
Leland Wilkinson is Chief Scientist at H2O, and Adjunct Professor of Computer Science at the University of Illinois at Chicago (http://www.cs.uic.edu/~wilkinson/). He wrote the SYSTAT statistical package and founded SYSTAT Inc. in 1984. Wilkinson is a Fellow of the American Statistical Association, a Fellow of the American Association for the Advancement of Science, and an elected member of the International Statistical Institute. In addition to journal articles and the original SYSTAT computer program and manuals, Wilkinson is the author of The Grammar of Graphics, the foundation for a number of commercial and open-source visual analytic systems (IBM-RAVE, Tableau, R-ggplot2, and Python-Bokeh).
Event Type
- NISS Hosted
- NISS Sponsored