10 Scientific Words You're Probably Using Wrong

In the course of a normal day, we may show a receipt as proof that we've paid for a service or be asked to show ID as proof of our age or identity. But ask a climate scientist or evolutionary biologist to "prove" that humans contribute to global warming or that Darwin was right all along and you may get an eye roll. Of course, the evidence for these widely accepted scientific beliefs is overwhelming, but most scientists will tell you that they aren't in the business of "proving" anything.

Here's why: Proofs are considered final. Evolutionary psychologist Satoshi Kanazawa argues that "proofs exist only in mathematics and logic" (some might add whiskey to that list), but not in science. In mathematics, once a proposition is proven, it becomes a theorem. (The square of the hypotenuse of a right triangle will always be equal to the sum of the squares of the other two sides. There's no gray area, and there's no need for Pythagoras to prove it again.)

Science, on the other hand, seeks to continually expand our understanding of the world, based on the principle that "any idea, no matter how widely accepted today, could be overturned tomorrow if the evidence warranted it" [source: University of California Museum of Paleontology]. Based on that possibility, nothing in science is considered proven.

Where does all that scientific evidence come from? Read on to find out.

If you've ever completed — or helped your kids with — a science fair project, you probably remember learning that your hypothesis should be a testable statement that can be supported or refuted through experimentation. But in everyday speech, we often use the word hypothesis to describe an educated guess. The two aren't entirely unrelated: Like an educated guess, a hypothesis is based on logic, observation and maybe even intuition, but the most important characteristic of a hypothesis is that it can be tested and the test, in turn, can be replicated.

A hypothesis is a scientist's attempt to provide a solution or explanation for a phenomenon that has not yet been explained [source: Zimmerman]. Of course, after reading the first scientific term on our list, you know that in science, a hypothesis is never "proved" to be correct; it's simply supported or refuted through repeated experimentation and observation – sometimes several decades' worth.

In the scientific method, a hypothesis is just the very first baby step toward formulating the next term on our list.

If you want to see smoke come out of a scientist's ears (figuratively speaking, of course), tell him or her that evolution (or gravity, for that matter) is "just a theory." In casual conversation, a theory may be just an idea, but in science, it's a system of ideas that stands up to repeated challenges.

Some people may try to dismiss widely accepted theories of global warming and evolution as merely speculative. But while a theory can never be "proven" (because this is science!), it's far from mere speculation. A scientific theory may incorporate several related hypotheses, gradually gaining acceptance only after being tested and supported through reproducible observation and experimentation [source: Zimmerman].

Another concept closely associated with a theory is a scientific law. One simple way to remember the two is that a law explains what will happen; theories seek to explain why it happens. Laws can often be expressed as mathematical equations. For example, Newton's law of gravity predicts what will happen if we drop an object, but it doesn't tell us why it happens. For that, we use Einstein's theory of general relativity [source: Krampf].

The next word on our list can be a helpful tool for testing a theory — but you probably use it to mean something else entirely.

When you use the word model in your day-to-day conversation, chances are you're referring to fashion, a toy airplane or an exemplar of good behavior ("a model student"). The term business model is sometimes used to explain the way a company plans to make money ("Sounds interesting, but what's their business model?") But scientifically speaking, a model is a tool that helps researchers predict how a system is likely to behave.

The word model can mean different things in different branches of science. In the behavioral sciences, for example, a model might refer to a set of conditions required for behavioral change to take place. And a physical model of the solar system is a simple way to demonstrate how the planets orbit the sun, while a mathematical model is a set of equations that represents a system. Economic models and climate models are both mathematical models, although they seek to predict and understand very different things. In scientific use, a model can be used to support a hypothesis if it generates the expected behavior. Often in modeling, some real-life factors are left out so as to isolate certain aspects [source: University of California Museum of Paleontology].

Our supermarket aisles are lined with foods, health and beauty products and cleaning solutions touting their all-natural and organic ingredient lists. But what do these terms really mean? Poison ivy is "natural," but you sure wouldn't want it in your salad — or your hand lotion, for that matter.

In the United States, the word "natural" as it pertains to food labels has no regulated definition. According the Food and Drug Administration (FDA), "It is difficult to define a food product that is 'natural' because the food has probably been processed and is no longer the product of the earth. That said, FDA has not developed a definition for use of the term natural or its derivatives. However, the agency has not objected to the use of the term if the food does not contain added color, artificial flavors, or synthetic substances." So that "natural" peanut butter you buy may be no better nutritionally than its "regular" counterpart.

The term organic is a bit better defined, as the U.S. Dept. of Agriculture (USDA) organic label means that a food has met a set of standards and requirements established by the USDA, including being grown without pesticides or synthetic fertilizer [source: Organic.org]. Of course, chemically speaking, all food is organic, since "organic" means carbon-based.

The next commonly misused word on our list takes us from natural and organic to nature vs. nurture.

Have you ever heard about a rare form of cancer or other unusual disease and asked whether it was "genetic"? Chances are, you were really wondering if it was passed down from a parent (inherited), as opposed to occurring out of the blue.

The word genetic simply means "of or relating to the genes" [source: Merriam-Webster]. All cancers are in fact genetic, in that they develop as a result of gene mutations, but only 5 to 10 percent are hereditary, or caused by genetic changes passed down from one generation to the next. Most of the rest — 70-80 percent — are known as sporadic cancers and are the result of genetic changes that occur during our lifetimes [source: MD AndersonCooper].

This word gets tossed around frequently, but not always correctly. We may hear that a new trend is "growing exponentially," or that a booming industry is experiencing "exponential growth," or even that one thing is "exponentially better" than another.

In everyday use, exponential has come to mean extremely large or rapid, but mathematically speaking, exponential growth simply means that something is growing at a rate proportional to its size. The rate of growth may be large or small. So if our economy grows at 0.1 percent a year, that's exponential growth, but it's hardly impressive [source: Safire].

Another common misconception is that if something is growing exponentially, it must be increasing by powers of 2, 3 and so on. If we hear that Earth's population is increasing exponentially, we may be horrified at the thought of 49 quintillion people suddenly fighting for resources. But exponential population growth means that the change in population over a given period of time is proportional to the population size. Right now that rate of growth is estimated to be around 1 percent per year, which works out to 70 million additional people [source: Annenberg].

The next scientific term on our list also relates to size.

A car company may boast that its latest and greatest model represents a "quantum leap" beyond anything else in its class. But while the manufacturer surely means to convince you that its newest sedan is a huge improvement over the competition, the word quantum means something entirely different to a physicist.

Scientifically speaking, a quantum is the smallest indivisible unit of energy [source: Rohrer]. Albert Einstein described photons as "quanta of light," meaning tiny, discrete particles, and in 1900, physicist Max Planck used the term quantum in his theory explaining the behavior of minute particles like photons and electrons at the subatomic level [sources: Quanta Magazine, Rohrer]. Suddenly that quantum leap doesn't seem like such a giant step forward. Indeed, a quantum leap would really be the tiniest change possible in an electron's energy level.

Of course, car commercials aren't the only place you'll hear the word quantum used questionably. One central principle of quantum mechanics is that material at the subatomic level can act as both a wave and a particle. But when an observer measures, for example, the exact position of a particle, the wave characteristics can no longer be observed [source: Swanson]. Self-help gurus like Deepak Chopra and Rhonda Byrne, the author of "The Secret," have oversimplified and misused this concept, incorrectly citing quantum physics as "proof" that observing something creates the thing —therefore we can will the things we wish for into existence simply by visualizing them [source: Swanson].

We all know that a percent is one part per 100, but things can get confusing when we talk about percentages without putting them in context. For example, a news report warned that "white women who get five or more blistering sunburns before the age of 20 have an 80 percent increased risk for melanoma." Eighty percent sounds huge, but since the American Cancer Society estimates the risk of developing melanoma at around 2 percent for women, an 80 percent increase puts the new risk at about 3.6 percent. So the absolute risk increases by 1.6 percentage points (or about 1.6 cases per 100 people), but the 80 percent jump in relative risk (i.e., risk compared with others in the study) is sure to get more headlines.

Marketers are masters at using percentages to sell products and ideas ("30 percent fewer calories!" "10% whiter!"). But quoting percentages without understanding where they came from can lead to all kinds of misinformation. Case in point: You've probably heard the myth that 50 percent of U.S. marriages end in divorce. The National Center for Health Statistics arrived at that figure by comparing the annual marriage rate per 1,000 people to the annual divorce rate [source: Hurley]. But since the people divorcing in any given year are not the same people who married that year, looking at the numbers for any one year doesn't really tell us anything.

I once had an oceanography professor who liked to point out that year after year, a spike in ice cream sales coincides with an increase in shark attacks. Should we conclude, therefore, that eating ice cream attracts sharks? Or that shark attacks lead to ice cream cravings? The true explanation, of course, is that ice cream sales and shark encounters are both linked with warmer weather. Aside from that shared association, the two have nothing to do with one another.

Just as any reputable scientist would avoid claiming that the results of an experiment "prove" a hypothesis, responsible researchers are careful not to conflate association or correlation with causation, even if preliminary research or casual observation seems to suggest a link between two events. If you were studying alcoholics and found that they were more depressed than non-alcoholics, you'd have to do more research before concluding that too much liquor makes a person depressed. Perhaps because the subjects were already depressed, they turned to booze to try and cheer themselves up. What work did they do and what were their family lives like? Did depression run in their families? The answers to those questions would allow you to make the leap (not quantum!) in your study from coincidence to cause-and-effect.