Monday, May 21st

Last update05:00:00 AM GMT

Webinars

Statistical Beauty: Visual analysis of economic data sets

Webinars > Statistical Beauty: Visual analysis of economic data sets

Statistics by themselves are often hard to understand and difficult to analyze objectively. The right software makes it possible to develop interactive information graphics that do more than dazzle: They help people truly understand and analyze the underlying data in large statistical databases.

This webinar uses a variety of macroeconomic data from the Organization for Economic Cooperation and Development (OECD) and the United Nations (UN) Statistics Division to demonstrate how to create truly useful and easy to understand analytical dashboards.

Even the most accurate and complete data set is useless if people cannot easily analyze and interpret its contents. The proper selection of data visualizations combined with best practices and use of color, size, layout and organization can make even the most dense material comprehensible. Beyond that, such information visualization tools can reveal hidden truths that may be obscured by the weight of controversial statistics.

As Edward Tufte pointed out in his book, Beautiful Evidence: "Making an evidence presentation is a moral act as well as an intellectual activity. To maintain standards of quality, relevance, and integrity for evidence, consumers of presentations should insist that presenters be held intellectually and ethically responsible for what they show and tell. Thus consuming a presentation is also an intellectual and a moral activity."

Viewers will learn:

  • How to create visual analytics dashboards that support fast discovery through clustering, outliers, correlations and contributions.
  • How to enhance analytical dashboards using calculations across time, through time and between set time windows.
  • How to use the special time series tools available in Panopticon's software to focus on a particular time slice or the performance across a defined time window and how to play back through all the data in a time series.