Posts Tagged ‘ Tests ’

In the name of diversity

March 9, 2017
By

I've said it in Numbersense (the chapter on school rankings), and here it happens again. According to the New York Times (link), Harvard Law School decided to allow applicants to submit GRE test scores instead of LSAT test scores. The announced purpose is to "encourage more students in the United States and internationally from a greater degree of disciplines to apply". The school has a fixed cohort size, 560 per…

Read more »

sigr: Simple Significance Reporting

March 7, 2017
By
sigr: Simple Significance Reporting

sigr is a simple R package that conveniently formats a few statistics and their significance tests. This allows the analyst to use the correct test no matter what modeling package or procedure they use. Model Example Let’s take as our example the following linear relation between x and y: library('sigr') set.seed(353525) d <- data.frame(x= rnorm(5)) … Continue reading sigr: Simple Significance Reporting

Read more »

Reader’s Guide to the Power Pose Controversy 3

November 2, 2016
By

This is the third and final post about the controversy over statistical analysis used in peer-reviewed published scholarly research. Most of the new stuff are covered in post #2 (link). Today's post covers statistical issues related to sample size, which is nothing new, but it was mentioned in Amy Cuddy's response to her critics and thus I also discuss it here. In post #2 (link), I offer the following mental…

Read more »

If you are practicing your power pose, stop now

September 29, 2016
By

Andrew and I warned you about "power poses" in Slate some time ago (link). Breaking news is that Dana Carney, a co-author of the paper that claimed the benefits of the power pose, has now confirmed that she no longer believes in the power pose. She is actively discouraging researchers from this "waste of time and resources." Here is her statement (PDF link), which is well worth reading in full.…

Read more »

Thank you Buzzfeed for noticing us humans

August 31, 2016
By

My friend John R. sent me this excellent Buzzfeed feature on music playlists. Here are some choice quotes to whet your appetite: In 2014, when Tim Cook explained Apple’s stunning $3 billion purchase of Beats by repeatedly invoking its “very rare and hard to find” team of music experts, he was talking about these guys. And their efforts since, which have pointed toward curated playlists (specifically, an industrial-scale trove of…

Read more »

It’s more important to know the source than the value of a number

July 12, 2016
By

Here we go again. ABC News reported that Ricky Williams, former NFL star, proclaimed himself as holding "the world record for most times drug tested". (link) He said he was tested 500 times. During this 11-year career, Williams failed the test four times. So there is one thing we know - the drug testing regime is not much of a deterrent. Since the athlete knows when he is juicing or…

Read more »

Tip of the day: don’t be Theranosed

May 23, 2016
By

Theranos (v): to spin stories that appeal to data while not presenting any data To be Theranosed is to fall for scammers who tell stories appealing to data but do not present any actual data. This is worse than story time, in which the storyteller starts out with real data but veers off mid-stream into unsubstantiated froth, hoping you and I got carried away by the narrative flow. Theranos (n):…

Read more »

Theranos and ethics

October 26, 2015
By

I have to admit I missed the hype about Elizabeth Holmes, and only learned about her from the Wall Street Journal hit job that came out last week (link). It feels like I arrived to the party after the police has shut the fun down! Holmes had been profiled in all the important places--no doubt many of her interviewers are feeling a bit red-faced. She dropped out of Stanford to…

Read more »

It is possible to not learn real causes from some A/B tests

July 20, 2015
By

It is conventional wisdom that A/B testing (or in proper terms, randomized controlled experiments) is the gold standard for causal analysis, meaning if you run an A/B test, you know what caused an effect. In practice, this is not always true. Sometimes, the A/B test only provides a statistical understanding of causes but not an average Joe's understanding. Let's start with a hypothetical example in which both definitions are aligned.…

Read more »

More on the AA paper

April 21, 2015
By
More on the AA paper

This is a supplement to the previous post about a new research paper on the effect of Alcoholics Anonymous, and an NY Times exposition that I commented on. A misreading of that article led me to complain about per-protocol analysis, which wasn't the methodology behind the Humphrey et. al. research. I will explain their methodology in this post (known as instrumental variables analysis). *** In the last post, I showed…

Read more »


Subscribe

Email:

  Subscribe