Statistical quote of the day

Englund

TS Contributor
#62
In the book Statistical Inference by Casella and Berger, there are a quote from Sherlock Holmes in the beginning of each chapter which I think is funny :)

Chapter one (Probability Theory) quote: "You can, for example, never foretell what any one man will do, but you can say with precision what an average number will be up to. Individuals vary, but percentages remain constant. So says the statistician." (Sherlock Holmes in The Sign of Four)
 

hlsmith

Omega Contributor
#63
Not statistical per se, but last night I read a great line (from somebody named Drexler at an English University). It was something like:

"computers are way more fundamental than the wheel"
 

noetsi

Fortran must die
#65
If you got drunk enough you can drown in six inches of water :p

I don't have the exact wording he used but Justice Scalia in rejecting the use of statistics in class action suits (a critical decision which gets little attention) argued that it had no validity in law because it was impossible to rule out alternative causes entirely with statistics.

While true, you wonder why the Supreme Court allows statistics to be used in trials at all (as it is) with that logic. Because by that logic statistics is pretty much useless.
 

Dason

Ambassador to the humans
#68
The subjectivist (i.e. Bayesian) states his judgements, whereas the objectivist sweeps them under the carpet by calling assumptions knowledge, and he basks in the glorious objectivity of science.
- I.J. Good
 

vinux

Dark Knight
#69
Some more bayesian quotes are

valid defense of using non-Bayesian methods, namely incompetence
Skilling

Inside every nonBayesian there is a Bayesian struggling to get out
Dennis V. Lindley

"good Bayesian does better than a non-Bayesian but a bad Bayesian gets clobbered."
Good


Some bayesians are like preachers, they take the credit to themselves and divert the blame to priors like preachers divert difficult questions to god
Richie (Some of our contributors know this person)
 

TheEcologist

Global Moderator
#71
I still don't know what to do about the compromise between how statistics
should be done and how journal editors seem to insist it should be done ...
-- Ben Bolker
R-sig-mixed-models (October 2008)
 

noetsi

Fortran must die
#72
As a former academic I think a better question is what percent of the people who use statistics for a living even know what baysian statistics is, let alone use it. I would suspect it is far less than one percent.

There is a trade off, outside academics, for improved results versus greater complexity. Most IMHO are going to chose the least complex method and are not going to use a methodology their boss will never have heard of in their one statistic course. I get lectures from my boss all the time for using overly complex methods or explanation and I don't even consider something like baysian which is never addressed in early statistics courses (actually I never encountered it even in a graduate program in measurement and statistics which included courses in SEM, ANOVA, HLM etc).

I have fallen far from the true faith of academics:p
 

Dason

Ambassador to the humans
#73
I always imagine your boss as a Dilbert-esq kind of character saying things like "We didn't hire you for your skill set! We hired you because I'm too lazy to run the incredible simple model myself!"
 
#74
I agree with Noetsi, as often!

I would even take away the word “Bayesian”.

As a former academic I think a better question is what percent of the people who use statistics for a living even know what [....] statistics is, let alone use it. I would suspect it is far less than one percent.
Standing on the ground, looking up on the giants, who are standing on other giants shoulders, and I realize that they can see an ocean of knowledge, and I can only see a small pond, I would be most happy if I had just a percent of their knowledge.




I always imagine your boss as a Dilbert-esq kind of character saying things like "We didn't hire you for your skill set! We hired you because I'm too lazy to run the incredible simple model myself!"
(The quote of the day!)

In 1930:ies R A Fishers boss wrote a book advocating deterministic allocation. The year after, Fisher wrote a book where he advocated randomisation – in contrast to his boss. It is not only Fishers brilliancy but also the qualities of his boss, that makes Fisher a famous person, and the rest of us not as famous.

The Dilbert bosses! (Choose your boss carefully!)
 

noetsi

Fortran must die
#75
In fairness my boss is a very bright person who also has organizational and intepersonal skills I only dream of. He has a doctorate in clinical psychology and has taught himself to be an expert in organizational change [where my doctorate is in, but which I have never actually worked]:p. He just has limited interest in statistics [and feels that senior leadership of which he is a part has even less -something I have noted myself from their comments].

Our organization thinks statistical analysis is important - but senior management has limited personal interest in it [which is strange to me]. That is why I was hired (although obviously I am not a statistician).

So is nothing really like the Dilbert boss. It is just that when I discuss his, likely very rational take, on the organization it is always in the context of statistics here. Even among academics, in my observation, really bright people are commonly disinterested in expert knowledge in other areas.
 

TheEcologist

Global Moderator
#76
Standing on the ground, looking up on the giants, who are standing on other giants shoulders, and I realize that they can see an ocean of knowledge, and I can only see a small pond, I would be most happy if I had just a percent of their knowledge.
This reminds me of some random wisdom I received one day:

"If I have not seen so far it is because I stood in giant's footsteps" - Linux Fortune

Which is inspiring, and a warning, sometimes focusing too much on what the great names of old have done, will blind you to what is obviously the best path forward now.

If you only follow great men, you will never leave their shadows.
 

noetsi

Fortran must die
#77
And if they are wrong you will never know. One thing that delayed the acceptance of general relativity among physicists (for which Einstein never won the Nobel prize for arguably the greatest discovery during the existence of that award) was the awe that Newton inspired. People simply accepted Newtonian physics even when theoretically and empirically it could be shown to be wrong.

Amusingly, or not, when Newton was the head of the Royal Society dealing with sciences he was a fierce reactionary who resisted new breakthroughs in science.
 

noetsi

Fortran must die
#78
Chatfield is one of my favorite statisticians in part because his focus in on practical analysis and he has a somewhat irrelevant view of the common academic wisdom. Here is one comment of his I found amusing.

"...SES is sometimes said to be applicable for series showing no seasonal variation or long term trend but with a locally constant mean which shows some 'drift' over time whatever that means." :p
 
#80
Once my professor told me this:

Based on zero property, zero divided by zero equals zero. Based on inverse property of multiplication, zero divided by zero equals one. Statistically, zero divided by zero should equal half based on the average.