One thing is common to all forms of science: an ultimate goal to know. Curiosity and inquiry are the driving forces for the development of science. Scientists seek to understand the world and the way it operates. To do this, they use two methods of logical thinking: inductive reasoning and deductive reasoning.
Inductive reasoning is a form of logical thinking that uses related observations to arrive at a general conclusion. This type of reasoning is common in descriptive science. A life scientist such as a biologist makes observations and records them. These data can be qualitative or quantitative, and he or she can supplement the raw data with drawings, pictures, photos, or videos. From many observations, the scientist can infer conclusions (inductions) based on evidence.
Inductive reasoning involves formulating generalizations inferred from careful observation and the analysis of a large amount of data. Brain studies provide an example (see image above). In this type of research, scientists observe many live brains. They do this while people are doing a specific activity, such as viewing images of food.
Scientists then predict the part of the brain that “lights up” during this activity to be the part controlling the response to the selected stimulus, in this case, images of food. The “lighting up” of the various areas of the brain is a consequence of excess absorption of radioactive sugar derivatives by active areas of the brain. A scanner observes the resultant increase in radioactivity. Then, researchers can stimulate that part of the brain to see if similar responses result.
Deductive reasoning or deduction is the type of logic used in hypothesis-based science. In deductive reason, the pattern of thinking moves in the opposite direction as compared to inductive reasoning. Deductive reasoning is a form of logical thinking that uses a general principle or law to forecast specific results. From those general principles, a scientist can extrapolate and predict the specific results that would be valid as long as the general principles are valid.
Studies in climate change (see image above) can illustrate this type of reasoning. For example, scientists may predict that if the climate becomes warmer in a particular region, then the distribution of plants and animals should change. Scientists have made and tested these predictions, and they have found many such changes, such as the modification of arable areas for agriculture, with change based on temperature averages.
Examples of Scientific Reasoning
The following are some examples of inductive and deductive reasoning (see image below).
Examples of Inductive Reasoning
Drawing a general conclusion from a number of observations:
- All flying birds and insects have wings. Birds and insects flap their wings as they move through the air. Therefore, wings enable flight.
- Animals as diverse as humans, insects, and wolves all exhibit social behavior. Therefore, social behavior must have an evolutionary advantage.
Example of Deductive Reasoning
Predicting specific results from a general premise:
- Insects generally survive mild winters better than harsh ones. Therefore, insect pests will become more problematic if global temperatures increase.
- Chromosomes, the carriers of DNA, separate into daughter cells during cell division. Therefore, DNA is the genetic material.
Two Pathways of Scientific Study
Both types of logical thinking are related to the two main pathways of scientific study: descriptive science and hypothesis-based science. Descriptive (or discovery) science, which is usually inductive, aims to observe, explore, and discover. On the other hand, hypothesis-based science, which is usually deductive, begins with a specific question or problem and a potential answer or solution that can be tested. The boundary between these two forms of study is often blurred, and most scientific endeavors combine both approaches. The fuzzy boundary becomes apparent when thinking about how easily observation can lead to specific questions.
For example, in 1941, Swiss engineer George de Mestral observed that the burr seeds that stuck to his clothes and his dog’s fur had a tiny hook structure. On closer inspection, he discovered that the burrs’ gripping device was more reliable than a zipper. He eventually developed a company and produced the hook-and-loop fastener popularly known today as Velcro (see image above). Generally, descriptive science and hypothesis-based science are in continuous dialogue.