Inductive reasoning is a logical process that concerns not only science, but also our daily lives. In a nutshell, inductive reasoning is essentially based on two main elements:
1) The certainty of observational data and information.
2) The conclusion. From data in our possession, we draw a general conclusion.
An example of inductive reasoning
Suppose we observe the presence of apple trees in some environmental related context. We will observe the presence of apple trees near a pond, around a lake, and on the banks of many rivers. A careful observation of these data provides evidence (and conclusion) that the apple trees grow in light and moist soils. The data that we have collected cannot be questioned by anyone. Anyone visiting the same places can check the rightness of our observations. Therefore, our conclusion [the apple trees grow best in light and moist soils] is true.
We come now to the logic-formal reasoning. We can say that the observed data (the apple trees) are the Premise of inductive reasoning (the apple trees grow well in X places). From these data, we can prove that our conclusions are absolutely true [the apple trees grow well in light and moist soils] , and they cannot be doubted. However, in inductive reasoning, even if the premises are true, the general conclusions may be false. We’ll look at one classic example many centuries ago suggested by various scientists to demonstrate that some conclusions are false. Stones of different weight and different size were dropped from the top of a tower to see if they fall at different speeds.
During X time a small piece of stone was dropped from the top of a tower. Then scientists dropped another stone even larger, and they noted that it took exactly the same time X. They therefore concluded that their speeds are equal. In this case the conclusion is true, but with reference only to the stones. In fact, the above-mentioned scientists did not experiment with other items. The result would have been very different if they dropped a feather down from the tower. Here we have a false conclusion, because there were too few data, and stones were only included in experiment. In this specific case, the premise is true (the stones), and the conclusion false [because they did not experiment with other items]. This means that if the scientists mentioned above would reach real conclusions, they would experience a large amount of information.
That’s why, at the end of inductive reasoning, we must always ensure data accuracy and completeness, and otherwise we may arrive at misleading conclusions, because the data are limited. Therefore, data accuracy and completeness are absolutely indispensable for reaching realistic conclusions. Otherwise appearances can deceive us, with the consequence that we may make wrong decisions.
We have to wait.
We need detailed information before deciding, and the pros and cons must be considered carefully. You can’t ignore any possibility, because one day you might say: “ I didn’t consider the consequences of my actions.” A ruinous decision might further aggravate the problem, and the affair becomes more complicated.
It is also true that sometimes we need quick reactions, but in this case the situation is absolutely different, because we don’t want to know the verity of a hypothesis, but we need only to decide rapidly how to react to an unforeseen and often sudden event.