December 2013
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Season's greetings from our team at StatSlice! In this issue, we present you with some of our most popular posts of 2013, including some past webinars & publications, and share some things we have learned in recent meetings or projects in a section entitled Heard Around the Water Cooler


We welcome your feedback for future issues, and we hope you have a safe and wonderful holiday.


The Management Team

StatSlice Systems


Popular Presentations from 2013
Webinar: Microsoft's GeoFlow Tool for Excel

On October 22, Brett Neuman, Manager Consultant at StatSlice Systems, delivered an informative webinar previewing Microsoft's GeoFlow tool for Excel. This webinar discusses features such as powerful 3D visualizations, geographic and temporal data, ways to create cinematic-quality guided tours, and packaging visualizations as part of an Excel workbook. Click here for more information.



Microsoft's GeoFlow Tool for Excel
Microsoft's GeoFlow Tool for Excel


 Visualizing University BI & Analytics Programs

This year, through extensive and on-going research, our team put together a report compiling information on BI & analytics programs at universities in the US & Canada. This report has received tremendous feedback, and we are currently undergoing major updates to be released in 2014. This Tableau visualization put much of our current information in perspective in many key ways. To read more, click here.



College QB Stats Visualizations


For all our football fans, in October, Justin Taylor published a blog with a visual breakdown of current NCAA quarterback stats in an effort to show off the athletic ability of Johnny Manziel who plays for his alma mater. To read the full blog, click here.


Heard Around the Water Cooler
The Importance of Being Na´ve


One of the first simplifying assumptions a scientist makes when studying a system is that nothing in the system interacts with anything else or that each object is independent. This seems like a fairly na´ve assumption because experience tells us that everything interacts with...well, everything else. However, there are a couple of major advantages that a scientist gains by making this assumption. One is that her equations for studying the system can be simplified greatly so that a low cost solution can be attained quickly. Another important advantage is that she now has a baseline that acts as a "sanity check" and can be compared with results from the more complicated interactive model. The example most people are familiar with from science is the Ideal Gas Model where the assumption is that the particles making up the gas do not interact with one another.


In the world of Data Mining, the Na´ve Bayes Model plays a similar role to the Ideal Gas Model because it provides a much faster and simpler way to calculate a model that gives us an idea of the predictive characteristics of a dataset. It also provides an easy way to check the results of the application of a much more complicated algorithm


Yet, what does independence mean in the context of data? 


Click here to read more from this post. 


Billy Decker, Consultant at StatSlice Systems

Happy Holidays From StatSlice
Hello Loyal Reader,

We would like to thank you for your continued readership throughout the year of 2013. We have many exciting projects in store for the coming year, and we're pleased that you will be the first recipients of our freshest content and ideas. Please view some of our 2013 webinars here, and feel free to email us with topics you would like to see covered in the future. Thank you again, and we hope you have a safe and wonderful holiday!
Jared Decker, Editor

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As a full-service data services consulting firm headquartered in Dallas, TX, we partner with our clients to deliver business intelligence and business analytics solutions that help solve their most complex needs.


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