Scientific Method for the Non-Scientist? Yes, please!

NextGen Voices is a feature of the premier science magazine, Science. It is designed as a series of surveys targeted towards young scientists, asking them questions on different aspects of life as a scientist that matters to them.(For some reason, it is not very well publicized, which is a pity – because I do think that NextGen Voices is offering young scientists an important platform to voice their opinions. I got to know about it only because my colleague in the lab, a subscriber to Science, showed it to me. This is partly the reason why I wanted to blog on this today – to raise awareness).

In 250 words or less, NextGen Voices asks young scientists:
What one big idea in your field do you wish that every non-scientist understood? Why?

I had a little time in between incubations [sigh!], and decided to quickly jot down a response. I am sure there would be many other worthy folks who would write awesome essays on what matters to them. I can’t compete with them. But this survey question immediately lit up a corner of my mind like the tree at the Rockefeller Center around Christmas time (see Postscript); that is to say, this topic – which is associated with communication and perception of science – is very dear to me. The following is what I wrote:

A scientific idea that I wish every non-scientist understood? Easy: “Scientific Method”, the foundation for rational, empirical, evidence-based understanding of the natural world; the central idea elegantly guiding how science works to advance knowledge.

To an enquiring mind, systematic observations of natural phenomena raise questions about their characteristics, antecedents and effects. To seek answers, the Method requires formulation of one or several ‘hypotheses’ – each a speculation about a phenomenon’s properties – including a ‘null hypothesis’, the idea that an observed phenomenon is merely a coincidental product of pure chance. Validity of each hypothesis is tested empirically by designing and conducting experiments with rigorous scientific controls, and analyzing generated data objectively to gather evidence.

A hypothesis unsupportable by evidence is modified (and retested), or discarded altogether, making way for alternative hypotheses. If supported by evidence, the hypothesis is accepted and forms the basis for asking new questions. Either way, this process continues recursively until there is a measure of confidence in the observations. Thus is born a ‘scientific theory’, a punctiliously arrived-at, confirmed and reliable explanation for natural phenomena.

Unfortunately, several key terms, ‘theory’ among them, have entered common parlance in a way that allows only their narrow, most restrictive definitions; for instance, ‘theory’ conjures up, to the lay mind, an image of unproven assertions. This severely hampers public perception of science’s accomplishments, leading to challenges to the credibility of scientific conclusions – as seen, for example, in the antagonism towards evolution, vaccines and global warming. This is eventually detrimental to the society.

For want of space (brevity ain’t my strong suite!), I couldn’t talk about another central idea, falsifiability or refutability. A hypothesis, in order to be valid, must be falsifiable, which means that whatever the hypothesis, it must be possible, at least in principle, to design an experiment whose outcome would completely contradict or refute the assertion made in it. For example, ‘All dogs are friendly’ is a testable, falsifiable hypothesis because it is logically possible that some dogs may not be friendly, and the actual finding of even one such canine would refute the hypothesis.

Why is this important? As human beings, even scientists may suffer from certain cognitive biases, including confirmation bias – a situation in which a preexisting belief in a given hypothesis pushes one to subconsciously filter observations in order to retain only those that are supportive of the hypothesis, even if the empirical reality demonstrates otherwise. An appropriate example of confirmation bias is an enduring belief in scientifically implausible propositions, such as homeopathy, in face of all evidence pointing otherwise.

By adhering to the principle of falsifiability, a scientist is obliged to strive to disprove a hypothesis, rather than prove it. This, along with an emphasis on reproducibility of results and the maintenance of strict controls during experiments, can adequately alleviate such cognitive biases, making the scientific conclusions that much stronger.

P.S. A glimpse of the 2004 Christmas Tree at the Rockefeller Center, New York City.

NYC Evening Out on X-mas Eve

P.P.S. Do add your voice by clicking on the NextGen Voices link at the beginning of this post. Don’t be alarmed if you reach a blank page with a message. They periodically close their polls for tallying and bringing out new questions. UPDATE: The survey results are out today, October 5, 2012.


  1. Anna Rasuna

    Nice article, thanks for sharing.

  2. Lee Turnpenny

    Right on, Kausik. It is the lack of appreciation of this ‘idea’ that opportunistic pseudoscience exploits, I think.

  3. Khalil A. Cassimally

    Imagine the scientific method being explained in the form of a story for a children’s book. The protagonist doesn’t have to be a scientist… a detective works just fine. He/She identifies a problem, thinks about what’s happening or what’s wrong, devises ingenious way to check what’s happening or what’s wrong before slowly patching his observations/clues together to come to the conclusion.

    Would be nice…

  4. Kausik Datta

    Nice article, thanks for sharing.

    Thank you for reading it, Anna.

    It is the lack of appreciation of this ‘idea’ that opportunistic pseudoscience exploits, I think.

    Lee, absolutely.

    Imagine the scientific method being explained in the form of a story for a children’s book.

    That is an absolutely BRILLIANT idea, Khalil! Y’know, in many ways, scientists are like detectives.

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.