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Jared Knowles
Works at University of Wisconsin
Attends University of Wisconsin-Madison
Lives in Madison, Wisconsin
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Submitted my dissertation for consideration to my dissertation committee on Tuesday. Hard to believe it's finished. Defense on 5/13, graduation on 5/15. 
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We are SO PROUD of you!
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In case you were thinking "machine learning -- isn't that just applied statistics?" -- here are the important differences you need to know :-)
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This is a good point about the hype of analytics outpacing the underlying data and research process. A good research background for analysts is essential so they can hear what their client wants and provide a best-case analysis using available data and whatever method is suitable for answering the question given data constraints. Machine learning only makes sense in some cases, in other cases, as the author states, "medians will do."
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This is a must read. This is about the best description I have read on what a "data scientist" is and why you would or would not to hire one. A good thing for applicants to keep in mind too when thinking about which jobs they are interested in. 
Introduction. Given the rise in the popularity of Data Science as of late, one only needs to be on recruiter mailing lists, look at company openings, or comb through Linkedin or Indeed's job postings to see that the Data Scientist position comes in a multitude of forms, some true to the name, ...
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Saw this band last weekend, and I just can't stop listening to this album. I don't know why -- it's catchy, hook-filled, and beautiful. Give it a spin. 
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Jared Knowles

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This is a great quick read. I'm not sure I'd settle in for the 600 page book, but I had no idea that the new SimCity managed to be so insightful about homelessness (intentionally, unintentionally?) by making it harder to eliminate than just building more houses. Sometimes games make great social commentary. 
A new 600-page, two volume epic about how to get rid of the homeless in SimCity.
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Did you catch the NPR Marketplace report highlighting early warning systems, including Wisconsin’s own?[http://www.marketplace.org/topics/education/learningcurve/using-data-predict-students-headed-trouble] WI has an early warning system designed to send warning signals to educators who can intervene before it is too late. DEWS—the Dropout Early Warning System—is a tool that provides a risk score for every 6th, 7th, 8th and 9th grader in the state. The risk score is a measure of the likelihood that the student will dropout of school or have an unplanned late graduation. Check out our new DEWS webpage and resources! [http://dpi.wi.gov/dews]
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It was a great piece on NPR.  Well done!
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Jared Knowles

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This is a really cool piece of science.
 
Saturn’s Iapetus looks like nothing else we’ve ever seen. What made it so?
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RStudio gets more awesome every day. This preview release looks to be a huge leap forward in productivity in R -- now you can rearrange editor panes like browser tabs!
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Great post on visualizing two-dimensional random effects.
Inspired by this post about visualizing shrinkage on Coppelia, and this thread about visualizing mixed models on Stack Exchange, I started thinking …
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Happy to have co-authored this project with +Zachary Deane-Mayer and glad to see it finally on CRAN.
 
caretEnsemble
My package caretEnsemble, for making ensembles of caret models, is now on CRAN: http://cran.r-project.org/web/packages/caretEnsemble Check it out, and let me know what you think! (Submit bug reports and feature requests to the issue tracker )
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"Deep learning" or neural networks may get all the press, but as I pointed out in our DEWS technical guide -- the heart and soul of a machine learning project happens well before the model is ever run. 
You probably know the famous scikit-learn algorithm cheat sheet. For fun, I revisited it a bit …
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283 people
Steve Scharre's profile photo
yiming lu's profile photo
Keda Wood Dyes's profile photo
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Alberto Negron's profile photo
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Education
  • University of Wisconsin-Madison
    Political Science, PhD, present
  • University of Wisconsin-Madison
    Political Science MA, 2008 - 2009
  • Pacific University
    Politics And Government; German Studies, 2004 - 2008
  • Ludwig-Maximillians Universitaet
    German, 2006 - 2007
Basic Information
Gender
Male
Birthday
May 25
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Story
Tagline
Political scientist, education researcher, and data visualizer.
Introduction

I am passionate about fulfilling the potential of applied statistical models and quality data visualization to inform policy makers and practitioners and improve the effectiveness of services - particularly in education. Since 2010 I have been exploring a number of different techniques to achieve these goals focusing on the methodology that best fits the needs of the audience. While working at the Wisconsin Department of Public Instruction, I have led a number of projects exploring this nexus of policy, practice, and evidence.

Major projects have included:

  • Developing and deploying a statewide Dropout Early Warning System (DEWS) in Wisconsin
  • Building training material in the R open-source statistical software DPI R Bootcamp
  • Assembling a diverse set of techniques for analyzing administrative data
  • Applying classification models to administrative records to determine natural groupings and patterns
  • Visualizing education data in unique ways to explore temporal, spatial, and correlational relationships For public examples of this work please visit the Presentations page.

I also believe in building techniques that scale. A big part of this is building partnerships and sharing work. It is this problem of scale that drives my interest in open platforms and open science. This includes developing shared open source tools on GitHub, building communities of practice within and across state lines, and professionalizing the analysis of administrative data for use by practitioners.

Leveraging administrative records to inform policy and practitioners involves investigating the appropriate methods that meet the needs of the users. Analytical methods are about the producing information from data, and the method chosen helps determine what information can be provided. I am continually searching for methods that meet those needs. Linear regression is not the beginning and end of data analysis and has many limits that policymakers and practitioners inherently understand. Currently I am very interested in investigating the application of the following methods:

  • Latent variable analysis including latent class analysis and structural equation modeling
  • Bayesian data analysis that includes incorporating the judgment of subject matter experts with data
  • Predictive modeling techniques including SVM, neural networks, and other classification algorithms
  • Mixed effect models that incorporate nested and crossed random effects
  • Variance decomposition

Once the analysis has been conducted, the challenge turns toward presenting the results in a way that is meaningful and actionable by educators. All too often important findings are buried in technical jargon, Greek letters, and incomprehensible tables filled with stars. Practitioners need visualizations that are engaging, meaningful, and make the complex workings of the analytical model accessible. I am interested in exploring the following approaches to this problem:

  • Simulation studies to dynamically explore model parameters
  • Multi-model inference to adjust models to different questions
  • Interactive displays of model results that can be controlled by intuitive UI elements
  • Building models into web applications using HTML5 and JavaScript

A final piece of this puzzle is building partnerships around key initiatives. This includes building partnerships within governmental entities and partnerships between governmental entities and external organizations. Selecting and building partnerships requires extensive communication and genuine commitment - but such work is vital. Quality partnerships allow partners to achieve economies of scale and more comprehensive investigations of problems and solutions. I currently participate in a number of such partnerships and am committed to identifying such opportunities and pursuing them in alignment with the needs of policymakers and practitioners.

Look for more information in the future as more of these projects roll out. Stay tuned!

Bragging rights
R Wizard
Work
Occupation
Research Analyst
Skills
R, presentations, data visualization, program evaluation, statistical analysis
Employment
  • University of Wisconsin
    Graduate Student, 2008 - present
  • Wisconsin Department Of Public Instruction
    Research Analyst, 2013 - present
  • Wisconsin Department of Public Instruction
    Policy Research Advisor, 2011 - 2013
  • Office of the Governor of Wisconsin
    Policy Analysis Intern, 2009 - 2010
Places
Map of the places this user has livedMap of the places this user has livedMap of the places this user has lived
Currently
Madison, Wisconsin
Previously
Laurel, Montana - Forest Grove, Oregon - Munich Germany - Helena, Montana
Jared Knowles's +1's are the things they like, agree with, or want to recommend.
Of Needles and Haystacks: Building an Accurate Statewide Dropout Early W...
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Of Needles and Haystacks: Building an Accurate Statewide Dropout Early Warning System in Wisconsin

Todo.txt
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Simple, fun to-do list manager syncs your todo.txt file to Dropbox.Countless apps and sites store your to-do list in their own proprietary d

xkcd: Reverse Identity Theft
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< Prev · Random · Next > · >|. Permanent link to this comic: http://xkcd.com/1279/ Image URL (for hotlinking/embedding): http://imgs.xkcd.co

PHD Comics: You can do that?
www.phdcomics.com

Link to Piled Higher and Deeper

Laurel man injured in motorcycle-deer collision on Molt Road
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A 32-year-old Laurel man riding a motorcycle suffered non-life-threatening injuries Friday after crashing into a deer that ran in front of h

Draft
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Draft is a versatile text editor for your Android smartphone and tablet. With Draft you can easily organise, edit and share all your notes.

Mike Levin
mikelev.in

A Director of Search Engine Optimization, Father and Newly Minted FOSS Advocate Living In New York City

What does this package look like?
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In this post, I give a very simple trick to understand the way a package is organized, which functions are included in and how these functio

Online resources for handling big data and parallel computing in R
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by Yanchang Zhao, RDataMining.com Compared with many other programming languages, such as C/C++ and Java, R is less efficient and consumes m

Interactive Graphics with the iplots Package (from “R in Action”)
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(This article was first published on R-statistics blog » R, and kindly contributed to R-bloggers) To leave a comment for the author, please

ACT to SAT M+V Concordance Chart in R
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For those of who work in Enrollment Management and routinely analyze higher ed data, I wanted to share an easy way to convert ACT to equival

Technical Analysis of Kansas Voter Registration Data
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Computer Assisted Reporting [Note:  Many of the links attached to images below are not working correctly.] This article describes technical

R Regression Diagnostics Part 1
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Linear regression can be a fast and powerful tool to model complex phenomena. However, it makes several assumptions about your data, and qu

Finding Earth II
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By 2030, we will have found approximately 10,000 exoplanets.

Getting Started with JAGS, rjags, and Bayesian Modelling
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This post provides links to various resources on getting started with Bayesianmodelling using JAGS and R.It discusses: (1) what is JAGS;(2)

How R Searches and Finds Stuff
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Or… How to push oneself down the rabbit hole of environments, namespaces, exports, imports, frames, enclosures, parents, and functi

Reproducible Research: Export Regression Table to MS Word
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Here's a quick tip for anyone wishing to export results, say a regression table, from R to MS Word:Read more »

David MacKay and Occam’s Razor « Statistical Modeling, Causal Inference...
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Statistical Modeling, Causal Inference, and Social Science. Skip to content. Home; Books; Blogroll; Sponsors; Authors; Feed. « Absolutely la

Example 9.17: (much) better pairs plots
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Pairs plots (section 5.1.17) are a useful way of displaying the pairwise relations between variables in a dataset. But the default display

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