Question 3 (Probably)

Hello again,

I’ve just put up the third question (although have managed to confusingly call it Question 2!) on YouTube

http://www.youtube.com/watch?v=RGcRoYgJpK0

I still seem to be performing my excellent party trick of moving my mouth seconds before I say anything!

The question concerns the use of ‘probability’ as the basis of science research. When responding to it, don’t get bogged down in the mathematical concept of Probability Theory (that’s something that only mathematicians with the brains the size of plants understand). I really want you to consider the wider implications of using methods and analyses that are tested against the probability that experimental outcomes are simply random. These days 95% (or more properly expressed 0.05) seems to be the ‘magic number’ for significance. In other words there is only a 5% chance that the observed difference between the experiment and the control was a fluke. You might like to think why 94% should not be significant…and let me know. The choice of significance level is down to the researcher. In biomedical sciences (where lives are at stake) we would expect very high probabilities to be used, say 99.99%. If we were analyzing the results of children’s academic performance (where lives are at stake) we would generally use lower probabilities. We don’t generally go below 95% which means “9 out of 10 cats say the prefer it” isn’t significant. Someone should tell Wiskas (apologies to Canadian students – it’s a famous cat food ad in the UK.)

We can never have 100% probability and the problem of course is that many non-scientists seemingly don’t understand this. Even the most exacting drug trial can only publish a probability that the drug works and/or is safe. This may be ridiculously high, but still may be seen by some (especially in the media) as presenting a risk. After all the researchers have implied that it is not 100% safe! Misunderstanding of science analysis is quickly transferred to a misunderstanding of maths when bottom line probabilities are turned into absolute values. Suddenly hundreds of people are at risk. Such general misunderstanding and deliberate misleading by the media (disasters sell papers) may spark all sorts of safety fears. Tony Blair famously refused to say whether his one year old son was to have the MMR vaccine (he did after a considerable delay) despite the government advocating its safety (http://www.timesonline.co.uk/tol/news/uk/article1033338.ece)

The fact that we operate in a world of probability seems to be confusing to a public that thinks we deal in certainty. If a patient, or a concerned parent, asked you ‘Is this drug 100% safe?’ how would you answer?

This then is the question. Is the MMR or the H1N1 vaccine safe? Start your response definitively – either yes or no, then add something to justify your decision.

I hope you enjoy your discussion.

Roger

Question 2: Falsification!

Ok folks,
Here it is question number 2 for you to ponder over the next two weeks, posted as a text question this time as I want to wanted to include a couple of links. This one explores falsification and the presentation of scientific findings, so here we go:
Falsifiability (or refutability) is the logical possibility that an assertion can be shown false by an observation or a physical experiment. In 1934 Karl Popper published “The Logic of Scientific Discovery” where he outlined the principles of the hypothetico-deductive scientific framework and a set of methodological rules called Falsificationism. Here he presents the idea that a thesis is “unscientific” (even if it were a false thesis) if we could not get rid of it by confronting it with an observation that contradicts it.
For example “antibiotics kill all micro-organisms” is scientific (even though obviously false) as we could test this and show this to be untrue (e.g. with a single case of a viral infection). It is therefore a scientific and falsifiable statement. On the other hand “Some witchcraft does cure illness” is unfalsifiable, and unscientific, as no amount of experimentation or observation could ever disprove the premise.
This idea of conjecture and refutation is an important one in science, and moves us beyond simple positivism. In science we develop ideas and theories through the observation of phenomena (inductive processes) and then propose theories to explain them, and then test our theories through (whenever possible) deductive processes. In this way we change our terms of reference and overthrow previously established orders as we move ahead with new knowledge (e.g. the Copernican revolution that changed our understanding of the Solar system).
We should then, be careful to consider the importance of both negative and positive data in science as the importance of publishing negative clinical studies is a vital part of the scientific process. It would be easy to ignore one side and focus on the ones that support our own pet theory. Given these thoughts what do you think of this story published recently in both US and UK newspapers with different viewpoints (see http://content.nejm.org/content/vol360/issue13/index.dtl for the papers they are based on)?
Take a look  at the stories at:
http://www.washingtonpost.com/wp-dyn/content/article/2009/03/18/AR2009031801623.html?hpid=topnews
and this one:
http://www.guardian.co.uk/society/2009/mar/18/prostate-cancer-screening-study
Lastly try and discuss in pairs and post a joint response, even if you don’t reach agreement! 🙂
Cheers Bernie
Ref:
Popper, Karl (1954) The Logic of Scientific Discovery, Basic Books, New York, NY

Ok folks,

Here it is question number 2 for you to ponder over the next two weeks, posted as a text question this time as I want to wanted to include a couple of links. This one explores falsification and the presentation of scientific findings, so here we go:

Falsifiability (or refutability) is the logical possibility that an assertion can be shown false by an observation or a physical experiment. In 1934 Karl Popper published “The Logic of Scientific Discovery” where he outlined the principles of the hypothetico-deductive scientific framework and a set of methodological rules called Falsificationism. Here he presents the idea that a thesis is “unscientific” (even if it were a false thesis) if we could not get rid of it by confronting it with an observation that contradicts it.

For example “antibiotics kill all micro-organisms” is scientific (even though obviously false) as we could test this and show this to be untrue (e.g. with a single case of a viral infection). It is therefore a scientific and falsifiable statement. On the other hand “Some witchcraft does cure illness” is unfalsifiable, and unscientific, as no amount of experimentation or observation could ever disprove the premise.

This idea of conjecture and refutation is an important one in science, and moves us beyond simple positivism. In science we develop ideas and theories through the observation of phenomena (inductive processes) and then propose theories to explain them, and then test our theories through (whenever possible) deductive processes. In this way we change our terms of reference and overthrow previously established orders as we move ahead with new knowledge (e.g. the Copernican revolution that changed our understanding of the Solar system).

We should then, be careful to consider the importance of both negative and positive data in science as the importance of publishing negative clinical studies is a vital part of the scientific process. It would be easy to ignore one side and focus on the ones that support our own pet theory. Given these thoughts what do you think of this story published recently in both US and UK newspapers with different viewpoints (see http://content.nejm.org/content/vol360/issue13/index.dtl for the papers they are based on)?

Take a look  at the stories at:

http://www.washingtonpost.com/wp-dyn/content/article/2009/03/18/AR2009031801623.html?hpid=topnews

and this one:

http://www.guardian.co.uk/society/2009/mar/18/prostate-cancer-screening-study

Lastly try and discuss in pairs and post a joint response, even if you don’t reach agreement! 🙂

Cheers Bernie

Ref:

Popper, Karl (1954) The Logic of Scientific Discovery, Basic Books, New York, NY