Confirmation Bias in Science

This post draws heavily on a New York Times article I stumbled across.  If you have a few minutes take the time to solve the problem presented and read the article.  I will post the rest of my thoughts farther down to not give any surprises.

http://www.nytimes.com/interactive/2015/07/03/upshot/a-quick-puzzle-to-test-your-problem-solving.html?_r=1&abt=0002&abg=1

Scroll down once you have solved the problem to continue reading. 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

This article brings up a very powerful term:  Confirmation Bias.    It is simply the fact that we love to hear the word "yes."   If i Google the definition I see:  

1. In psychology and cognitive science, confirmation bias (or confirmatory bias) is a tendency to search for or interpret information in a way that confirms one's preconceptions, leading to statistical errors.

The article has some pretty staggering facts to show confirmation bias is real.

   Remarkably, 78 percent of people who have played this game so far have guessed the answer without first hearing a single no. A mere 9 percent heard at least three nos — even though there is no penalty or cost for being told no, save the small disappointment that every human being feels when hearing “no.”

 The article's focus is on how confirmation bias comes into play in politics or corporate America.  However I also see it come into play in the field of science.  The fundamental use of science is based on finding evidence to accept or reject an idea.   Science never truly proves anything since new evidence may be found as new experiments or technologies come online.  But scientists are humans too and confirmation bias is rampant.  Many times we only hear about the positive results of a study or an idea and not the failures.    Just look at a science publication and see how many papers talk about a negative result where an idea is rejected.  These "failures" happen all the time, but they are not the ones that get the spotlight.   Most talk is about the positive results only even though negative results can bring just as much value to a person or organization.  It goes back to the notion we like to hear yes and the negative results are not celebrated with an equal weight.  I really liked this article since it is a good reminder that yes is not always the best answer.   

My results are below.  While I may have looked for negative results in this simple example I realize I need to keep a handle on confirmation bias especially in the field of science.   We all want that breakthrough in science, not the "failure" of an experiment.  But it may be that failure that gives you the right answer.

If your interested in this topic, here is some other thoughts on this puzzle:

http://theness.com/neurologicablog/index.php/a-quick-logic-lesson/