Arriving at a general assertion by looking at examples is called
The correct answer and explanation is:
The correct answer is inductive reasoning.
Inductive reasoning is the process of drawing general conclusions from specific examples or observations. It involves taking a limited set of data points and extrapolating them to form broader generalizations or theories. This type of reasoning is common in everyday decision-making as well as in scientific research, where conclusions are made based on patterns or trends that emerge from specific observations.
For example, if you observe that the sun has risen in the east every day of your life, you might use inductive reasoning to conclude that the sun always rises in the east. This generalization is based on repeated specific instances, although it is not guaranteed to be true in every possible situation (e.g., if the Earth’s rotation changes).
Inductive reasoning differs from deductive reasoning, where a conclusion is derived from a set of premises that are assumed to be true. In deductive reasoning, the conclusion is guaranteed to be true if the premises are valid. On the other hand, inductive reasoning only leads to probable conclusions, and these conclusions can be revised or refined as new evidence emerges.
In scientific research, inductive reasoning is used when researchers observe patterns in the data and then develop hypotheses or theories to explain those patterns. Theories developed through inductive reasoning are often tested further through experiments or observations to see if they hold up under different conditions.
While inductive reasoning is a powerful tool, it does have limitations. The conclusions drawn may not always be accurate or reliable, especially if the examples or observations are limited or biased. Therefore, it’s important to consider the strength and representativeness of the examples used in inductive reasoning.