Data Science Statistics Articles, Guide, and Tutorials

Decentralized Triggered Secret Release

Modeling Statisticsposted by David Chudzicki March 26, 2018

Intro Have you ever had to confront a villain with your discoveries, knowing that unless you take precautions they might just kill you? Or gone on a dangerous adventure, wanting to keep the details secret until you come back (or unless you don’t)? Or wanted your... Read more

Tidy Resampling Redux with Agricultural Economics Data

Modeling Statisticsposted by Max Kuhn March 21, 2018

(No statistical graphs in this one. This is what my dog Artemis looks like when she wants my attention during work hours.) Mindy L. Mallory (@ace_prof) wrote a blog post on Machine Learning and Econometrics: Model Selection and Assessment Statistical Learning Style where she has a great description... Read more

Support for gun control is decreasing in all age groups

Modeling Statisticsposted by Allen Downey March 9, 2018

This is the third article in a series about changes in support for gun control over the last 50 years. In the first article I looked at data from the General Social Survey and found that young adults are less likely than previous generations to support gun control.... Read more

Post-Columbine students do not support gun control

Modeling Statistics Data analysis|statisticsposted by Allen Downey March 7, 2018

In their coverage of the Parkland school shooting, The Economist writes: Though polling suggests that young people are only slightly more in favour of gun-control measures than their elders, those surveys focus on those aged 18 and above. There may be a pre- and post-Columbine divide within that... Read more

Support for gun control is lower among young adults

Modeling Statistics Data analysis|statisticsposted by Allen Downey March 5, 2018

In current discussions of gun policies, many advocates of gun control talk as if time is on their side; that is, they assume that young people are more likely than old people to support gun control. This letter to the editor of the Economist summarizes the argument: It... Read more

What are data science and machine learning?

Deep Learning Modeling Research Statistics Data Science|Machine Learningposted by Sebastian Raschka February 27, 2018

Let’s start with machine learning In short, machine learning algorithms are algorithms that learn (often predictive) models from data. I.e., instead of formulating “rules” manually, a machine learning algorithm will learn the model for you. So, let me give you an example to illustrate what that... Read more

SEINFELD CHARACTERS – A POST ABOUT NOTHING

Data Visualization Modeling R Statistics Tools & Languagesposted by Scott Stoltzman February 24, 2018

This post is dedicated to my mother – Seinfeld’s greatest fan. Seinfeld is a classic TV sitcom. It featured four main characters surrounded by relatively normal, everyday, run of the mill scenarios. In the spirit of Seinfeld, this post will also “be about nothing.” Load Required... Read more

What’s the healthiest city in the US? (and what does that even mean?)

Modeling Predictive Analytics Statistics Data analysis|Healthcare|Healthcare Data Scienceposted by Marcelo Rinesi February 22, 2018

(Spoiler alert: it’s not Detroit, and it’d be a relatively simple question if it weren’t for cancer.) The human body has multiple ways of not working well; at its broadest, the CDC’s 500 Cities project data set lists fourteen different health outcomes, from arthritis, to stroke,... Read more

Random Forest Classification of Mushrooms

There is a plethora of classification algorithms available to people who have a bit of coding experience and a set of data. A common machine learning method is the random forest, which is a good place to start. This is a use case in R of the randomForest package used... Read more

Deep Learning for Disaster Recovery: Automatic Detection of Flooded Roads

Data Visualization Modeling Predictive Analytics Statistics AI|Artificial Intelligence|Deep Learning|Machine Learningposted by Jack Kwok February 20, 2018

Jack Kwok is a Software Engineer with 15 years of professional experience. At Insight, he built a Deep Learning solution to automatically detect flooded roads during natural disasters. He is now a Software Engineer at Lyft working with Machine Learning and Deep Learning. Want to learn... Read more