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Elder Research Data Science and Predictive Analytics Blog

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Elder Research Data Science and Predictive Analytics Blog

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  • Paul Derstine
  • March 15, 2017 12:52:18 AM
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A Little About Us

Elder Research is a recognized leader in the science, practice, and technology of advanced analytics. Topics on our blog cover analytics tips, analytical modeling, data and text mining tools, data visualization, analytics best practices, case studies, etc. to provide business leaders with actionable information on real world analytics problems.

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    Models make predictions by identifying consistent correlations in what has been observed, but we usually require more than predictions to know what action we should take. For example, knowing that older people are more likely to have heart disease is a good first step, but knowing behaviors or treatments that will reduce the risk of heart disease as we age is actionable. Knowing millennials are more likely to buy your product than gen Z is nice, but knowing which marketing approach will...

    shutterstock_1615848271

    Models make predictions by identifying consistent correlations in what has been observed, but we usually require more than predictions to know what action we should take. For example, knowing that older people are more likely to have heart disease is a good first step, but knowing behaviors or treatments that will reduce the risk of heart disease as we age is actionable. Knowing millennials are more likely to buy your product than gen Z is nice, but knowing which marketing approach will persuade gen Z to buy is valuable. In this election season, knowing who will vote is interesting, but identifying unlikely voters who can be persuaded to show up at the polls is everything to campaign managers. When data science goes further to estimate the impact of alternative actions we may perform to achieve a better outcome, we call it uplift modeling or, more technically, treatment effect modeling. For this instructional blog we will use a very limited example of how uplift modeling can apply to get-out-the-vote campaigns, without divulging which sample or geography was used.


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    BLOG_Building a Successful Analytics Project from the Ground Up

    Like a house built to withstand the seasons, a successful and sustainable analytics project must start with a firm foundation, a purposeful plan, a seasoned team, and the right tools and materials. Analytics project owners and budget-holders, much like a homeowner, want to see their large investment result in something that delivers value and supports evolving needs.


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    As the Chief Data Officer (CDO) role gets established at each federal agency as required by the Evidence-Based Policymaking Act of 2018 (Public Law 115-435) (Evidence Act), I can’t help but feel conflicted. On one hand, I am excited that the federal government has taken such an intentional step towards a more data-driven government: There are enormous potential benefits when CDOs partner with program owners to innovate and deliver real values to the federal government and our citizens. On...

    Pioneers Logo

    As the Chief Data Officer (CDO) role gets established at each federal agency as required by the Evidence-Based Policymaking Act of 2018 (Public Law 115-435) (Evidence Act), I can’t help but feel conflicted. On one hand, I am excited that the federal government has taken such an intentional step towards a more data-driven government: There are enormous potential benefits when CDOs partner with program owners to innovate and deliver real values to the federal government and our citizens. On the other hand, I am concerned this role, if not properly supported and empowered, could become yet another silo yielding little real value.


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    BLOG_New Tool Helps States Reduce Unemployment Insurance Overpayment

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    The blog Recidivism, and the Failure of AUC published on Statistics.com showed how the use of “Area Under the Curve” (AUC) concealed bias against African-Americans defendants in a model predicting recidivism, that is, which defendants would re-offend. There, a model varied greatly in its performance characteristics depending on whether the defendant was white or black. Though both situations resulted in virtually identical AUC measures, they led to very different false alarm vs. false...

    BLOG_AUC - A Fatally Flawed Model Metric-1

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