experimental. the behavioral risk factor surveillance system (brfss) aggregates behavioral health data from 400,000 adults via telephone every year. it's um *clears throat* the largest telephone survey in the world and it's gotta lotta uses...
380 search results for "SQL"
Data Science, Data Analysis, R and Python
The October 2012 issue of Harvard Business Review prominently features the words “Getting Control of Big Data” on the cover, and the magazine includes these three related articles:
- “Big Data: The Management Revolution,” by Andrew McAfee and Erik Brynjolfsson, pages 61 – 68;
- “Data Scientist: The Sexiest Job of the 21st Century,” by Thomas H. Davenport and D.J. Patil, pages...
What is Correctness for Statistical Software?
Introduction A few months ago, Drew Conway and I gave a webcast that tried to teach people about the basic principles behind linear and logistic regression. To illustrate logistic regression, we worked through a series of progressively more complex spam detection problems. The simplest data set we used was the following: This data set has
analyze the american community survey (acs) with r and monetdb
experimental. think of the american community survey (acs) as the united states' census for off-years - the ones that don't end in zero. every year, one percent of all americans respond, making it the largest complex sample administered by ...
Please stop using Excel-like formats to exchange data
I know “officially” data scientists all always work in “big data” environments with data in a remote database, streaming store or key-value system. But in day to day work Excel files and Excel export files get used a lot and cause a disproportionate amount of pain. I would like to make a plea to my
How to spend an inordinate amount of time becoming efficient
I’ve spent a good deal of 2012 constructing a data warehouse to manage all the various data elements that my company has. Although we’re a small enterprise, the richness and complexity of the information is rather high. Moreover, as a data-driven organization, there’s a strong impetus to construct meaningful analysis with every bit of input 
Importing Data Into R from Different Sources
I have found that I get data from many different sources. These sources range from simple .csv files to more complex relational databases, to structure XML or JSON files. I have compiled the different approaches that one can use to easily access these datasets. Local Column Delimited Files This is probably the most common and
R FAQs for the fresh starters
R, which was largely predominant in the academic world, has started picking up a lot in businesses as well. At least that is what I am witnessing among my colleagues. Lot of people have started experimenting with R, choosing the path to enlightenment. ...
analyze the basic stand alone medicare claims public use files (bsapufs) with r and monetdb
the centers for medicare and medicaid services (cms) took the plunge. the famous medicare 5% sample has been released to the public, free of charge. jfyi - medicare is the u.s. government program that provides health insurance to 50 million...
Exchange Data between Python and R with SQLite
SQLite is a light-weight database with zero-configuration. Being fast, reliable, and simple, SQLite is a good choice to store / query large data, e.g. terabytes, and is well supported by both Python and R.
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
