Deductive reasoning happens when a researcher works from the more general information to the more specific.
Sometimes this is called the “top-down” approach because the researcher starts at the top with a very broad spectrum of information and they work their way down to a specific conclusion.
For instance, a researcher might begin with a theory about his or her topic of interest.
From there, he or she would narrow that down into more specific hypotheses that can be tested.
The hypotheses are then narrowed down even further when observations are collected to test the hypotheses.
This ultimately leads the researcher to be able to test the hypotheses with specific data, leading to a confirmation (or not) of the original theory and arriving at a conclusion.
An example of deductive reasoning can be seen in this set of statements: Every day, I leave for work in my car at eight o’clock.
Every day, the drive to work takes 45 minutes I arrive to work on time.
Therefore, if I leave for work at eight o’clock today, I will be on time.
The deductive statement above is a perfect logical statement, but it does rely on the initial premise being correct.
Perhaps today there is construction on the way to work and you will end up being late.
This is why any hypothesis can never be completely proved, because there is always the possibility for the initial premise to be wrong.
Inductive reasoning works the opposite way, moving from specific observations to broader generalizations and theories.
This is sometimes called a “bottom up” approach.
The researcher begins with specific observations and measures, begins to then detect patterns and regularities, formulate some tentative hypotheses to explore, and finally ends up developing some general conclusions or theories.
An example of inductive reasoning can be seen in this set of statements: Today, I left for work at eight o’clock and I arrived on time.
Therefore, every day that I leave the house at eight o’clock, I will arrive to work on time.
While inductive reasoning is commonly used in science, it is not always logically valid because it is not always accurate to assume that a general principle is correct.
In the example above, perhaps ‘today’ is a weekend with less traffic, so if you left the house at eight o’clock on a Monday, it would take longer and you would be late for work.
It is illogical to assume an entire premise just because one specific data set seems to suggest it.