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In professions like cosmetology, teaching, business, and mechanics, inductive reasoning allows professionals to improve decision-making based on past outcomes.

Analogical reasoning relies on identifying similarities between familiar situations and new or unfamiliar ones.

Causal inference involves reasoning about what might have caused an observed effect.

Analogical reasoning relies on identifying similarities between familiar situations and new or unfamiliar ones.

Inductive generalization moves from observations about a sample to conclusions about a larger population.

Inductive reasoning discourages adaptability because it relies only on past experiences rather than new information.

Causal inference involves reasoning about what might have caused an observed effect.

Sign reasoning depends on direct proof rather than clues or indicators that suggest a possible conclusion.

Inductive reasoning involves making predictions or conclusions based on patterns, observations, or prior experiences.

A retail company uses a Decision Tree to predict whether a customer will make a purchase after receiving a promotional email. The training set is large and the model has been built so that the tree is deep with less than 5 customers in each leaf node. Answer both questions below: 1. Explain why this model might perform poorly on new, unseen customer data. 2. Then, describe a potential business risk the company could face if it uses this model to decide which customers to target in future campaigns.