Critical Thinking #9

 Critical Thinking  #9   Explanations

By definition, explanations start with a conclusion and then propose a reason for why that is so. The difference between an argument and an explanation is significant but often difficult to recognize. Maybe this will help. An argument asks: how do you know that? An explanation tells us why something is so. Casual explanations suggest particular physical or behavioral phenomenon--one thing causes another. Explanations begin with hypotheses and work their way through implausible to plausible explanations. Explanations look at evidence and use it to evaluate the hypotheses.

There are helpful qualities of explanations that contain general standards to guide our thinking and use. For example, explanations should be consistent, internally (logical) and externally (not contradict the natural world). A second standard is falsifiability. They must always be able to withstand scrutiny and remain truthful. Thirdly, the scope of the explanation must be sufficiently inclusion so as not to focus on an exception rather than a rule. Simplicity is always the best guide. The more complex an explanation, the more difficult it is to comprehend and drag in irrelevant information. And last, harking back to our look at fallacies, explanations legitimately use causality instead of correlation.

Scientific explanations are a category all their own. This process of thinking uses causal explanations and hypotheses to discover empirical facts. The heart of this process, the driving force, is the scientific method. If the subject interests you, I recommend Ian Barbour's Religion and Science for a fascinating history of its development. The scientific method is a universally accepted and used process in human kind's search for understanding of the natural world. It involves a five step process:

identify the problem

gather evidence and make observations

form a hypothesis

test the hypothesis--over and over

analyze the results objectively

Beware of bias that leads to false conclusions. Science does not evaluate subjective interpretations or value judgments. Learn the difference between science and pseudoscience.

Statistics are another category. Distinguish between qualitative and quantitative surveys. If you use them, they must be reliable and valid. Surveys can be: too small, biased, use manipulative questions, be based on guesswork, and miss contextual information.

There is a practical application for all this. For example, applied critically, you would understand that vaccines do not cause autism and covid vaccinations do not cause sterility.