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+--- Thread: Abandoning 'statistically significant' + Modeling shifting beliefs in complex society (/thread-2968.html)
Abandoning 'statistically significant' + Modeling shifting beliefs in complex society - C C - Oct 21, 2016
It’s time for science to abandon the term ‘statistically significant’
https://aeon.co/essays/it-s-time-for-science-to-abandon-the-term-statistically-significant
EXCERPTS: The aim of science is to establish facts, as accurately as possible. It is therefore crucially important to determine whether an observed phenomenon is real, or whether it’s the result of pure chance. If you declare that you’ve discovered something when in fact it’s just random, that’s called a false discovery or a false positive. And false positives are alarmingly common in some areas of medical science. [...] The problem of how to distinguish a genuine observation from random chance is a very old one. It’s been debated for centuries by philosophers and, more fruitfully, by statisticians. It turns on the distinction between induction and deduction. Science is an exercise in inductive reasoning: we are making observations and trying to infer general rules from them. Induction can never be certain. In contrast, deductive reasoning is easier: you deduce what you would expect to observe if some general rule were true and then compare it with what you actually see. The problem is that, for a scientist, deductive arguments don’t directly answer the question that you want to ask....
Modeling shifting beliefs in a complex social environment
https://www.sciencedaily.com/releases/2016/10/161020142252.htm
RELEASE: A new model is allowing scientists to explore how changing an individual's certainty in the belief on the truth of one statement leads to changes in their beliefs on the truth of others. This tool could help to answer questions about individuals' likelihoods of being persuaded to a new belief. People rarely form opinions by merely accepting or rejecting the social consensus of others, studies have shown.
For example, individuals who reject evolutionary theory and humanmade climate change may be aware of the scientific consensuses on these subjects, but reject the ideas anyway, as other, complex social and environmental factors influence their ultimate opinions.
Here, using a model designed to represent social influence among individuals with multiple beliefs, Noah Friedken and colleagues provide a step toward understanding this phenomenon.
Their work extends the so-called Friedkin-Johnson model, which explores how individuals form opinions in complex circumstances, by better accounting for the power of underlying beliefs (for example, the belief that human civilization is too insignificant to alter the global environment, which may prevent someone from believing in humanmade climate change).
Friedkin and colleagues incorporate an "intrapersonal" influence mechanism in their modeling framework, in which acceptance of one proposition influences the acceptance of others. Using this framework, the researchers performed a theoretical test that looked at what happened when beliefs regarding the trustworthiness of evidence on the existence of weapons of mass destruction in Iraq changed in the U.S., and how that in turn impacted views on whether the invasion of Iraq was justified.
They characterized how beliefs, either held by a few or many, can influence interpersonal networks. The work is further explored by Carter Butts in a related Perspective.