Ever been to a soccer game and have someone ask you what foul the “umpire” just called? Or how many “points” does the blue team have? Certain terms go with certain sports. The same is true for science, so if you want to sound like a scientist, learn these words and use them correctly.
• Theory: Many people use “theory” when they mean “idea”. For example, when someone says “I have a theory about that”, they usually mean they have an idea or a thought or a possible explanation. In science a theory is a well tested, widely supported, explanation of a natural phenomenon accepted as true by most scientists in that field. Examples include the Theory of Island Biogeography, The Theory of Evolution by Natural Selection, and Einstein’s Theory of Relativity. Generally, your science project is not creating a new theory so try not to use “theory” in the project unless you are explaining a specific theory behind the phenomenon you are testing.
• Experiment: Along the same lines, many people use “experiment” when they mean “try out”. You may hear someone say “I’m going to experiment with a new recipe tonight”. In contrast, scientists use experiment for a well designed test of a hypothesis.
• Significant: Here is another problematic word. We often use significant to mean “meaningful” or “substantial”, but to a scientist, significant specifically means you conducted a statistical evaluation of the data and found mathematical support for or against your hypothesis. At the elementary (and middle) school levels, this is well beyond their grade level and unless the student can explain how the statistics are justified and the underlying assumptions, you should not use the term significant. Warning: if a judge asks a student if “the results were significant”, the judge is evaluating the student’s knowledge of this term.
• Prove/Proof: It would be exceptionally rare for a student’s science fair project to prove anything and the idea of “proving” something in science is not the same as “prove” in a court of law. Stay away from this word too. It would be better to state “My results provide evidence for…” or “My results demonstrate that…”
• Causation vs. Correlation: With a well designed experiment, it may be tempting to conclude that the change in the independent variable caused the change in the dependent variable. Here again, there are agreed upon rules for claiming causation. For environmental projects with more than one variable measured, be wary of correlation vs. causation.
A creative example of this is the conclusion that eating ice cream causes shark attacks. A survey in most areas would show that as ice cream sales increase, the number of shark attacks increases. The reality is these variables are both related to a third variable (temperature). In the summer, with higher temperatures, both ice cream sales and shark attack cases (because more people go in the water) would be expected to increase independently of each other.
• Accurate vs. Precise: These words are often used as synonyms, but have specific meanings in science. Accuracy is a measure of how close the data is to the real value and precision is a measure of how repeatable the measurement is. The concepts are often illustrated with a bull’s eye diagram.