« Data is the next frontier of equal rights | Main | Why are GMAT scores going up? »

Comments

Feed You can follow this conversation by subscribing to the comment feed for this post.

Ken

My experience with diagnostic testing in medicine is that it isn't easy and the trade-offs aren't obvious to clinicians and they should be. Ask a question about acceptable rates of false positives and there will probably be a blank look. This is even though in one case the positive test result would involve referral to a specialist and they usually aren't happy with seeing patients with no disease.

There is also a lot of bad analysis even from statisticians. Ignoring verification bias will make the test look better. I've been to a talk on identifying illegal imports where verification bias wasn't even mentioned. Verification bias is where only a portion of the sample have the gold standard test applied. Ignore it and there is lots of missing data, and not missing completely at random as most of the imports to be fully assessed are those that show as high risk.

The comments to this entry are closed.

Kaiser Fung. Business analytics and data visualization expert. Author and Speaker.
Visit my website. Follow my Twitter. See my articles at Daily Beast, 538, HBR.

See my Youtube and Flickr.
Numbers Rule Your World:
Amazon - Barnes&Noble

Numbersense:
Amazon - Barnes&Noble

Search3

  • only in Big Data

Next Events

Jan: 10 NYPL Data Science Careers Talk, New York, NY

Past Events

Aug: 15 NYPL Analytics Resume Review Workshop, New York, NY

Apr: 2 Data Visualization Seminar, Pasadena, CA

Mar: 30 ASA DataFest, New York, NY

See more here

Courses

R Fundamentals, Principal Analytics Prep

Numbersense: Statistical Reasoning in Practice, Principal Analytics Prep

Applied Analytics Frameworks & Methods, Columbia

The Art of Data Visualization, NYU

Signed copies at McNally-Jackson, NYC

Excerpts: Numbersense Ch. 1, 7, 8. NRYW

Junk Charts Blog



Link to junkcharts

Graphics design by Amanda Lee

Community