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Statistics

Soccer player predicted as the top rising star - back in November (video)

May 11, 2016 by Jure Rejec

Did you know that Big Data can help us predict who the future soccer stars will be? This is precisely what happened in Riyad Mahrez’s case, PFA Player of the Year, who has conquered the English Premier League with Leicester City.During last year’s Big Data Week Conference in London, Malta-based entrepreneur Valery Bollier correctly...[read more]

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Big Data in the Sports Industry

December 23, 2015 by Trisha Miller

Professional athletes everywhere are being asked to wear tech that will track their every move and download patterns of their stats. Will this help to improve the game or could the usage of big data destroy sports as we know it?[read more]

Google’s Acquisition Spree

October 30, 2015 by Nilesh Jethwa

There is a history of partnerships and acquisitions which has made Google a truly successful technology company. Using the list of all Google acquired companies and kpi dashboard tool we illustrate Google's acquisition journey.[read more]

Fantasy Sports Betting: The Next 'Big Thing' Thanks to Big Data

June 16, 2015 by Jure Rejec

Big data is revolutionizing the sports betting industry and this is just the beginning. While it may seem that European Fantasy Sports hasn't really picked up as yet, since Europe is known as a historically late adopter, the future looks promising for soccer lovers who seek richer experiences than what is being offered at the moment by well established betting operators.[read more]

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Problems with the Language of Probability

April 6, 2015 by Paul Barsch

Risky Business column.

Using probabilistic terminology to communicate the “likelihood” of an event occurring to those untrained in understanding such terms, can in some instances lead to the ruin of careers, companies and in worst cases—loss of life.[read more]

How to Position Big Data

February 11, 2015 by Martyn Jones

Position big data.

Fueled by the new fashions on the block, principally Big Data, the Internet of Things, and to a lesser extent Cloud computing, there's a debate quietly taking please over what statistics is and is not, and where it fits in the whole new brave world of data architecture and management. For this piece I would like to put aspects of this discussion into context, by asking what 'Core Statistics' means in the context of the DW 3.0 Information Supply Framework.[read more]

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The World’s Largest, Fastest, Most Agile Supply Chain

December 31, 2014 by Keith Peterson

Supply chain.

There is one shipping firm in the world, maybe the galaxy, that is counted on more than FedEx, UPS, and DHL combined. In fact, this organization has an even more complex supply chain. It takes its own orders, makes its own goods, and ships them all in one night.[read more]

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Employee Analysis: How Growth in Employee Strength Relates to Profits

December 11, 2014 by Nilesh Jethwa

Employee analysis.

In this article, we will perform some analysis on the employee related metrics from the top tech companies. All of the top tech companies are selected based on their current market capitalization with the exception of Yahoo. The year 2014 is not included as part of this analysis.[read more]

Who Gets the Call When Your Analytics Process Crashes?

October 10, 2014 by Bill Franks

Analytics matters.

I recently had a meeting with one of the largest companies in the world, where we discussed concerns about ongoing maintenance and, more importantly, ongoing repair required for analytics processes. The conversation helped solidify in my mind a major disconnect that often occurs when organizations deploy an analytics process into a production setting. Let’s walk through that disconnect here.[read more]

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Can Fossil Analysis Software Help Us Plan Curriculum?

August 20, 2014 by J. Kevin Byrne

Fossil analysis software.

Paleontologists use (free) software (known as PAST) for their statistical analysis. I bumped into it via key-word web-search to support academic planning I was doing. I offloaded it, took a close look, and I discovered I could use a specific menu within it (hierarchical analysis) to help reconceptualize curriculum at my design college.[read more]

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A Quick Guide to Structured and Unstructured Data

June 28, 2014 by Michele Nemschoff
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Guide to structured and unstructured data.

Big data has opened doors never before considered by many businesses. The idea of utilizing unstructured data for analysis has in the past been far too expensive for most companies to consider. Thanks to technologies such as Hadoop, unstructured data analysis is becoming more common in the business world.[read more]

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When Ideology Reigns Over Data

June 2, 2014 by Paul Barsch

Risky Business column.

Increasingly, the mantra of “let the data speak for themselves” is falling by the wayside. There are dangers to reputations, companies and global economies when researchers and/or statisticians either see what they want to see—despite the data, or worse, gently massage data to get “the right results.”[read more]

Job Market Explodes for Quantitative Students

May 22, 2014 by Linda Burtch

Jennifer Priestley, Professor of Statistics and Data Science at Kennesaw State University.

With the market for quantitative candidates continuing to gain momentum, Burtch Works spoke with Jennifer Priestley, Professor of Statistics and Data Science at Kennesaw State University - and friend of Burtch Works - about the job market for statistics majors, the beginnings of her MS in Applied Statistics program, and her thoughts on SAS vs. R.[read more]

SAS vs. R: The Deeper Dive

May 7, 2014 by Linda Burtch

SAS vs. R.

Last month, I conducted a quick “flash survey” of my network and asked: Which do you prefer to use, R or SAS? I posted the initial results on my blog a few weeks ago, and as promised during the webinar for our Data Scientist Salary Study, we’ve finished up our deeper dive analysis of the data from over 1,000 respondents.[read more]

Mobile Advertising, Clustering Algorithms, and Your Ticket for a Free Ride

May 4, 2014 by Lillian Pierson

Mobile advertising and clustering algorithms.

Because of some pretty bad-ass data science and Google’s ever-increasing awesomeness, it looks like one day in the not too distant future, we will all be able to get a free (or heavily-discounted) ride. A taxi ride, that is.[read more]