Types of Inductive Reasoning

1. Generalization

Generalization is defined as “a form of inductive reasoning that draws conclusions based on recurring patterns or repeated observations” (Miller and Poston 615). Generalization occurs when multiple instances of behavior are observed and general conclusions are formed by the observer based on the observed commonalities between instances. 

With generalization comes the risk of overgeneralization. This is a common issue when conclusions are made hastily, or the language used to describe the commonalities is imprecise. An example of imprecise language is "badly." A better choice might be "inadequately," "unsatisfactorily" or similar. 

Using poor word choice or making conclusions too quickly can also lead to stereotyping. Merriam-Webster defines stereotyping as "a standardized mental picture that is held in common by members of a group and that represents an oversimplified opinion, prejudiced attitude, or uncritical judgment" (Merriam-Webster n.p.). Correct use of generalization avoids hasty generalization through sound logic and large sample sizes of observations. If too small of a sample is the entire bases of generalization, conclusions may not be accurate. 

2. Causal Reasoning

Causal reasoning is defined as “a form of inductive reasoning that seeks to make cause-effect connections” (Miller and Poston 616). According to Chris Miller and Mia Poston, good causal reasoning must demonstrate that the cause has "a direct relationship on the effect" and is "strong enough to make the effect" (616). In other words, there can be numerous causes of an effect, but usually some causes influence the effect more or are more likely to occur.

Students using causal reasoning are susceptible to mistaking correlation for causation. However, students should be careful not to confuse the two, as correlation does not equate to causation. Correlation is simply an observed relationship between two factors; two related observations are not necessarily causes of each other.

Example 1: Stormy weather caused the power outage. 

This is a GOOD example of causal reasoning. Stormy weather has caused many power outages historically, thus storms are directly related to and strong enough to cause power outages. 

Example 2: The squirrel nibbling on the electrical insulation last week caused the power outage. 

This is a MEDIOCRE example of causal reasoning. While the weakened electrical insulation may have contributed to the power outage, the squirrel likely was not a main cause of the power outage. If the squirrel was the direct cause, the power outage probably would have occurred immediately after the squirrel chewed the electrical insulation, which also suggests that the squirrel was not strong enough to cause a power outage on its own. Thus, the squirrel as a cause fails both the test of directness and the test of strength. 

Example 3: A storm was occurring during the power outage, therefore power outages cause storms.

This is a BAD example of causal reasoning. In this example, correlation is confused with causation. Although power outages and storms are correlated, power outages evidently do not affect the weather.

3. Sign Reasoning

Sign reasoning is defined as “a form of inductive reasoning in which conclusions are drawn about phenomena based on events that precede or co-exist with (but not cause) a subsequent event” (Miller and Posto, 617). The concept of sign reasoning is similar to correlation, in that "signs" are related to each other because they occur simultaneously. However, signs are not necessarily causes of each other.

Example 1: More caffeinated drinks are being sold, and more students are studying at the UU. Therefore, finals week has begun.

This is a GOOD example of sign reasoning. An increased number of sold caffeinated drinks and an increased number of students studying at the UU are signs indicating the start of finals week.

Example 2: During finals week, more caffeinated drinks are sold, and more students study at the UU. Therefore, selling caffeinated drinks causes students to study at the University Union. 

This is a BAD example of sign reasoning. An increased number of sold caffeinated drinks does not inherently cause an increased number of students studying at the UU, and vice versa. Instead, they are effects of the cause, finals week.

4. Analogical Reasoning

Analogical reasoning includes analogies made to compare phenomena or objects to another (Miller 617). However, analogies must be made about two objects that are similar enough in essential ways. The phrase “apples and oranges” is common when dismissing an analogy because of the inherent differences between phenomena because they are not similar enough to warrant a comparison. 

To warrant an analogical comparison, the two objects being compared must be similar enough to have a valid comparison. This brings into question the reliability of analogical reasoning, because there is no universal metric to decide how similar objects or situations must be. This form of reasoning is subject to personal bias and logical flaws. The "apples and oranges" example highlights this issue specifically, as this phrase tends is used to dismiss improper analogy, however apples and oranges do share actual similarities. They are both fruits, and for some, this might be enough to compare them. This type of inductive reasoning is commonly used, but caution must be taken when choosing objects to compare so that no illogical or fallacious analogies are made. 

Fallacies Associated with Inductive Reasoning

1. Historical Fallacy

A historical fallacy is "an error of interpretation in which one reads into a process, either as a cause or an essential element, what only comes about as the result of the process" (APA, n.p.). In colloquial terms, hindsight may be the term used to describe this fallacy conversationally. 

For example, someone claims a certain outcome was obvious based on warning signs, but fails to realize that these warning signs were only obvious after the outcome has occurred. 

Some have stated that the attack on Pearl Harbor during World War II was obvious because of all of the signs leading up to the attack, but these signs were only noted after the attack had happened. None of the "warning signs" were specified before the attack, and thus the argument that the outcome was obvious is no longer true. 

2. Slippery Slope

A slippery slope argument is made of three parts:

(1) an acceptable decision

(2) a dangerous outcome

(3) the way the decision leads to the outcome

(Walton, 275)

Often with inductive reasoning, slippery slope fallacies arise when there is lacking evidence or gaps of reasoning within an argument.

Example 1: If someone leaves work five minutes late, they will be stuck in traffic for four hours because of rush hour.

With suitable evidence, this may be a valid claim. Since there is no evidence supporting this claim other than "rush hour", the claim has become a fallacy.

Example 2: At six o'clock, the work day for all the offices on this street are done for the day. If someone leaves at 6:05, they will be stuck in traffic as all the other cars leave the parking garage. 

This provides suitable evidence for why leaving five minutes late could cause someone to be stuck in traffic. However, this is not an example of inductive reasoning.

Example 3: Susie left work at 6:05. She was stuck in traffic for two hours because the offices close at 6:00. Therefore, if Susie leaves for work at 6:05, they will be stuck in traffic.

This claim provides suitable evidence for why leaving five minutes late could cause someone to be stuck in traffic. It is also an example of inductive reasoning because it combines a special case with a general principle.

3. False Cause (or Post Hoc)

In a false cause fallacy, also known as a post hoc fallacy, an author assumes that "when two events occur one after the other... the first event caused the second (Goverment of Canada, n.p.). This assumption is fallacious unless there is substantial evidence to prove a cause-effect relationship between the two events.

Example 1: The pedestrian walked under a ladder, then tripped on the sidewalk five minutes later. Therefore, walking on sidewalks must be unlucky.