Slate has a good article on some good consumer critical thinking about statistics

Slate has a good “article”:http://www.slate.com/id/2150354/?nav=ais on how to think about whether you should take a drug. In the confusing world of “relative risk vs. absolute risk”:http://www.randomjohn.info/wordpress/2006/05/03/lying-with-statistics-relative-risk-vs-absolute-risk/, it’s really hard to know the effect of a drug.
Enter the NNT(Number Needed to Treat). The idea behind this number is the _expected_ number of people that you would [...]

Lying with statistics in the news

How did I miss this one? You can find many examples of lying with statistics at Stats.org, which seems to be a non-profit associated with George Mason University (the Tar Heel in me says boo-hiss). Given they are a non-profit associated with a university (even if they are a small operation), they have much greater [...]

Bad statistics and science at MDS

The FDA sent a “warning letter”:http://www.fda.gov/cder/warn/2006/MDS_Pharma.pdf to a company called MDS Pharma late last month (posted to the agency’s website yesterday) basically saying that MDS Pharma lied with statistics. (Please note that I have not seen or review the company’s response.) Apparently, the agency found the following issues:
* Studies weren’t appropriately auditible
* The company failed [...]

Significance, statistical and otherwise

In chasing down the perfect p-value (p<0.05), we can sometimes forget the overall objective of performing a clinical trial. You can have the best-designed study in the world with all the statistical issues carefully considered, and the trial can succeed, but if your trial result isn’t _important_, or _clinically significant_, then the statistical significance means [...]

Gelman posts his chapter on ‘Lying with statistics’

Andrew Gelman, a prominent Bayesian statistician, has posted a chapter ‘”Lying with Statistics”:http://www.stat.columbia.edu/~cook/movabletype/archives/2006/07/using_numbers_t.html’ from his book.
A good read, with good examples.

Statistical critique: where do we draw the line? (An application to drug safety analysis)

I just read an interesting entry (and thread) on Andrew Gelman’s statistical blog that goes along the lines of some questions I have been pondering lately. Specifically, these two paragraphs hit me (this is form an email to Gelman):

The whole spirit of your blog would have led, in my view, to a rejection of the [...]

Lying with statistics: pretty pictures

Statistics show that 88% of people now get their statistics education from RandomJohn.info! What, you don’t believe me? Here’s the proof! With my new parter DataNumerics.com, I will strive to bring you the most impressive statistics ever!
(h/t Insider aka FRIDAY!)
PS. Don’t read the fine print. Never EVER read the fine print.
Technorati Tags: statistics

Lying with statistics: linkage

I’ve found a few recent posts about lying with statistics:
Skewing Statistics for Politics
This entry over at Good Math is about the selective reporting of statistics to make your argument look better but ignoring other statistics that make your argument look wrong. In the meantime, he takes on Powerline.
Anti-mercury warriors descending further into the depths
While I [...]

When statistics can’t tell the truth, a followup application to the Vioxx controversy

I’ve avoided posting on the Vioxx controversy for a long time, but I would be amiss if I discussed drug safety without discussing the hot button issue of the day that has brought drug safety to the forefront.
My earlier thesis is
Clearly, closely adhering to the rules of statistics isn’t going to get anyone very far [...]

Lying with statistics: when statistics can’t tell the truth, or why I’m interested in the statistics of drug safety (and an application to the thimerosal-autism controversy)

Drug safety is hard to study. There are so many things that can go wrong with the human body. To statistically analyze every single possible thing that can go wrong is impossible. There are thousands of possible adverse events, a whole lot of laboratory measurements that have to be taken (so we can address, among [...]