Scientific Versus Everyday Reasoning

Each day, people offer statements as if they are facts, such as, “It looks like rain today,” or, “Dogs are very loyal.” These conclusions represent hypotheses about the world: best guesses as to how the world works. Scientists also draw conclusions, claiming things like, “There is an 80% chance of rain today,” or, “Dogs tend to protect their human companions.” You’ll notice that the two examples of scientific claims use less certain language and are more likely to be associated with probabilities. Understanding the similarities and differences between scientific and everyday (non-scientific) statements is essential to our ability to accurately evaluate the trustworthiness of various claims.

Scientific and everyday reasoning both employ induction: drawing general conclusions from specific observations. For example, a person’s opinion that cramming for a test increases performance may be based on her memory of passing an exam after pulling an all-night study session. Similarly, a researcher’s conclusion against cramming might be based on studies comparing the test performances of people who studied the material in different ways (e.g., cramming versus study sessions spaced out over time). In these scenarios, both scientific and everyday conclusions are drawn from a limited sample of potential observations.

The process of induction, alone, does not seem suitable enough to provide trustworthy information—given the contradictory results. What should a student who wants to perform well on exams do? One source of information encourages her to cram, while another suggests that spacing out her studying time is the best strategy. To make the best decision with the information at hand, we need to appreciate the differences between personal opinions and scientific statements, which requires an understanding of science and the nature of scientific reasoning.

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Table 1. Features of good scientific theories (Kuhn, 2011)

There are generally agreed-upon features that distinguish scientific thinking—and the theories and data generated by it—from everyday thinking. A short list of some of the commonly cited features of scientific theories and data is shown in Table 1.

One additional feature of modern science not included in this list but prevalent in scientists’ thinking and theorizing is falsifiability, a feature that has so permeated scientific practice that it warrants additional clarification. In the early 20th century, Karl Popper (1902-1994) suggested that science can be distinguished from pseudoscience (or just everyday reasoning) because scientific claims are capable of being falsified. That is, a claim can be conceivably demonstrated to be untrue. For example, a person might claim that “all people are right handed.” This claim can be tested and—ultimately—thrown out because it can be shown to be false: There are people who are left-handed. An easy rule of thumb is to not get confused by the term “falsifiable” but to understand that—more or less—it means testable.

On the other hand, some claims cannot be tested and falsified. Imagine, for instance, that a magician claims that he can teach people to move objects with their minds. The trick, he explains, is to truly believe in one’s ability for it to work. When his students fail to budge chairs with their minds, the magician scolds, “Obviously, you don’t truly believe.” The magician’s claim does not qualify as falsifiable because there is no way to disprove it. It is unscientific.

Popper was particularly irritated about nonscientific claims because he believed they were a threat to the science of psychology. Specifically, he was dissatisfied with Freud’s explanations for mental illness. Freud believed that when a person suffers a mental illness it is often due to problems stemming from childhood. For instance, imagine a person who grows up to be an obsessive perfectionist. If she were raised by messy, relaxed parents, Freud might argue that her adult perfectionism is a reaction to her early family experiences—an effort to maintain order and routine instead of chaos. Alternatively, imagine the same person being raised by harsh, orderly parents. In this case, Freud might argue that her adult tidiness is simply her internalizing her parents’ way of being. As you can see, according to Freud’s rationale, both opposing scenarios are possible; no matter what the disorder, Freud’s theory could explain its childhood origin—thus failing to meet the principle of falsifiability.

Popper argued against statements that could not be falsified. He claimed that they blocked scientific progress: There was no way to advance, refine, or refute knowledge based on such claims. Popper’s solution was a powerful one: If science showed all the possibilities that were not true, we would be left only with what is true. That is, we need to be able to articulate— beforehand—the kinds of evidence that will disprove our hypothesis and cause us to abandon it. Karl Popper was an influential thinker regarding scientific theory and reasoning.

 

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 [Image: Lucinda Douglas-Menzies, https://goo.gl/ uuqxCe]

This may seem counterintuitive. For example, if a scientist wanted to establish a comprehensive understanding of why car accidents happen, she would systematically test all potential causes: alcohol consumption, speeding, using a cell phone, fiddling with the radio, wearing sandals, eating, chatting with a passenger, etc. A complete understanding could only be achieved once all possible explanations were explored and either falsified or not. After all the testing was concluded, the evidence would be evaluated against the criteria for falsification, and only the real causes of accidents would remain. The scientist could dismiss certain claims (e.g., sandals lead to car accidents) and keep only those supported by research (e.g., using a mobile phone while driving increases risk). It might seem absurd that a scientist would need to investigate so many alternative explanations, but it is exactly how we rule out bad claims. Of course, many explanations are complicated and involve multiple causes—as with car accidents, as well as psychological phenomena.

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Test Yourself 1: Can It Be Falsified?

Which of the following hypotheses can be falsified? For each, be sure to consider what kind of data could be collected to demonstrate that a statement is not true.

Chocolate tastes better than pasta.

We live in the most violent time in history.

Time can run backward as well as forward.

There are planets other than Earth that have water on them.

[See answer at end of this module]

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Although the idea of falsification remains central to scientific data and theory development, these days it’s not used strictly the way Popper originally envisioned it. To begin with, scientists aren’t solely interested in demonstrating what isn’t. Scientists are also interested in providing descriptions and explanations for the way things are. We want to describe different causes and the various conditions under which they occur. We want to discover when young children start speaking in complete sentences, for example, or whether people are happier on the weekend, or how exercise impacts depression. These explorations require us to draw conclusions from limited samples of data. In some cases, these data seem to fit with our hypotheses and in others they do not. This is where interpretation and probability come in.

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UPEI Introduction to Psychology 1 by Philip Smith is licensed under a Creative Commons Attribution 4.0 International License, except where otherwise noted.

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