Inductive arguments aim at probability, not guarantee
An inductive argument is strong when its premises make the conclusion reasonable to accept, even though the conclusion might still turn out false. That is the first major shift from deductive thinking. Deductive arguments aim at necessity: if the premises are true, the conclusion must be true. Inductive arguments aim at well-supported likelihood: if the premises are true, the conclusion is probably true, but not certainly so.
This matters because students often downgrade every non-guaranteeing argument as if it has failed. In logic, that is a mistake. If the evidence is broad, representative, and relevant, then an inductive argument can be excellent even though it remains defeasible. Consider a weather forecast that predicts rain with 90 percent probability based on satellite imagery, barometric pressure, and historical patterns. The forecast could be wrong, but that does not make it a poor inference. It is a strong inference with a small residual risk.
The practical upshot is that we need two different scorecards. For deductive arguments, we ask: do the premises guarantee the conclusion? For inductive arguments, we ask: do the premises make the conclusion likely enough to guide action or belief? Treating inductive arguments by the deductive standard leads to the error of dismissing good evidence simply because it falls short of proof.
To build intuition, compare these two arguments side by side. Deductive: All mammals are warm-blooded; whales are mammals; therefore whales are warm-blooded. Inductive: Every whale biologist has observed over the past century reports that whales are warm-blooded; therefore whales are probably warm-blooded. The deductive version is valid by its logical form. The inductive version is strong because of the breadth and consistency of the evidence, but it remains revisable if startling new data appeared.