5 strategies for converting Big Data into actionable insights
The strategy to turn the raw data into actionable insights is to integrate and analyze data from all data sources to reach better and optimized business decisions. The word “big” in big data refers to the huge volume of data involved. Big data technologies aim at storing, analyzing, querying,... Read more
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 passwords to be... Read more
Tidy Resampling Redux with Agricultural Economics Data
(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 of the variance-bias... Read more
Support for gun control is decreasing in all age groups
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. In the second article I... Read more
Post-Columbine students do not support gun control
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 group. Based on... Read more
Support for gun control is lower among young adults
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 is unlikely that... Read more
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 means! Say you... Read more
SEINFELD CHARACTERS – A POST ABOUT NOTHING
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 Libraries library(scales) library(RMySQL)... Read more
What’s the healthiest city in the US? (and what does that even mean?)
(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, to the wonderfully... 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 on a data... Read more