Science Test Topic 3 – Free
Deductive vs. Inductive Reasoning
In science, one can develop explanations from two different perspectives. One perspective is to start from the “bottom up.” You would broadly make observations, describe patterns, and construct an explanation. This is called inductive reasoning. In inductive reasoning, you work from the specifics, and generalize from those specifics.
Inductive reasoning can be understood through the following example:
- Tom has had an allergic reaction to peanuts, walnuts, and stir hazelnuts.
- All of these food items are nuts.
- Therefore, Tom is probably allergic to all nuts.
Another perspective is to work from the “top down.” You would start with an understanding of a scientific theory, and then use that understanding to make a hypothesis about a specific situation. This is called deductive reasoning. In deductive reasoning, you work from generalizations to the specifics. You can think of deductive reasoning as testing existing theories and hypotheses (generalizations) by collecting experimental observations (specific examples) that put those ideas to the test.
Deductive reasoning can be understood through the following example:
- Every citrus fruit is a good source of vitamin C.
- This thing in my hand is a caracara orange (a kind of citrus fruit).
- Therefore, this caracara orange is a good source of Vitamin C.
Correlation versus Causation
Remember that science can serve many purposes, such as description, classification, explanation, and prediction. However, when many people are asked to describe the purpose of science, they will say to explain why something happens, or to establish cause and effect. Indeed, one of the most powerful aspects of science is in its ability to establish causal, or cause and effect, relationships.
However, one public misconception about science is that all scientific explanations establish causation. Even when science can predict something, it does not mean that the causal relationship has been established. Consider the following popular example of the difference between causation and correlation:
Taken from: http://cdn.searchenginejournal.com/wp-content/uploads/2012/06/Correlation-637×451.jpg
There is a well-established relationship between the consumption of ice cream (let’s say, measured in number of ice cream cones eaten), and the number of deaths by drowning. One can predict the number of drowning deaths from the number of ice creams consumed. However, ice cream consumption is not the cause of the drowning deaths (any more than the drowning deaths cause an increase in the amount of ice cream consumption). While ice cream consumption and drowning are correlated, the warm temperatures of summer are what lead to both increased ice cream consumption and the increased rate of deaths by drowning. Consider the following diagram:
Taken from: https://lh4.googleusercontent.com/6YtJyuoykTQx3EgxkWeaK1v5QQEYR8ACSvDUj_L9LWNFA87E1I2PzIR7fjBv-J9C1cQ98JJIgHf-HcfpeMoezX2zZusOekrWZHxQjg9hVTdnnh8noRimx_pn1A
When a scientist says that there is a relationship between two things, it does not necessarily follow that they are saying that one thing causes another. This is a misconception that many people have when reading the results of scientific studies or listening to scientific findings in the media.