A tale of two types of journalism
Building Data Science in Healthcare
Many tech companies have complete control over the format of the data they collect. Healthcare, which relies on external data about patients and their interactions, has no such luxury. Ian Blumenfield, Head of Data Science at Clover Health, shares how they handle messy data and the other unique data challenges the industry faces. - Clover Health
PyData London Conference Presentations
A few weekends ago PyData hosted a conference in London, and they just released videos and slides of a bunch of the presentations. Here’s one of our favorites: Statistically Solving Sneezes and Sniffles - a Work in Progress. - PyData
How to Make Reps Care About Data Quality
When a sales rep fails to record information about her activities or clients, it can lead to incomplete and inaccurate reports and forecasts. These tips and tricks will help sales leaders encourage reps to be vigilant about consistently logging data. - InsightSquared
Easier data analysis in Python with pandas
A series of video tutorials for pandas newbies who know some Python. Each video answers a student-posed question using real-world data. - Data School
People are talking about: data journalism drama
A tiff between Nate Silver and The New York Times broke out last week*. *It all started when Jim Rutenberg published a column in The New York Times that criticized FiveThirtyEight’s incorrect prediction of the Indiana Democratic primary results. Nate Silver fired right back on FiveThirtyEight’s podcast.
This tension between data journalism and shoe-leather reporting might feel familiar to anyone who’s struggled with balancing data- and intuition-based decision making.
- The Republican Horse Race Is Over, and Journalism Lost (The New York Times)
- Elections Podcast: Paul Ryan Isn’t Happy (FiveThirtyEight)
- Nate Silver unloads on The New York Times (Columbia Journalism Review)