Inductive Reasoning: Types, Pros and Cons

We conduct one logic exercise almost every day, even if we aren't aware of it. Inductive reasoning is the process through which we take small items we've seen or read and infer general ideas from them.

 

This type of thinking is very useful in writing. However, there is a significant difference between a strong and a weak inductive argument.

 

 

What is Inductive Reasoning?

 

Inductive reasoning, also known as inductive logic, is a style of reasoning in which a general conclusion is drawn from a collection of specific observations. Inductive reasoning is sometimes referred to as "bottom-up" logic since it entails expanding individual premises into bigger generalizations.

 

Inductive Reasoning is a type of reasoning in which the premises (statements) are considered as offering some evidence but no guarantee for drawing the conclusion. The assertions include particular instances that you may have witnessed or experienced, as well as information that you know to be true or inaccurate. 

 

Inductive reasoning is used to derive results by combining observations with experiencing information and prior knowledge. Your conclusion may not always be correct, but it should be logical based on the evidence you utilized. 

 

Inductive reasoning is a "bottom-up" approach that involves establishing broad assumptions based on particular premises. Inductions are typically formed subconsciously, yet they have a significant impact on our behaviors and beliefs. 

 

For example, an introduction may claim that everyone at a party was wearing blue shirts, and because Laura was there, she was wearing a blue shirt. Inductive reasoning is a critical thinking talent that many organizations want in their workers. It exemplifies soft analytical abilities, which are concerned with how you engage with ideas, social settings, and people.

 

When you make a choice, you usually go through a subconscious process of filtering observations based on your previous experiences. For example, if you glance outdoors and see a sunny sky, you could conclude that you don't need an umbrella. 

 

It is a logical assumption because numerous previous sunny days have shown this reasoning right. This is an example of inductive reasoning, which is a logical process based on unique experiences, observations, or facts.

 

Also Read | Hypothesis Testing

 

Examples of Inductive Reasoning

 

1. A marketing manager examines the tactics of other rivals in similar situations and discovers a method that has usually resulted in greater conversions. He then employs the same approach in her campaigns.

 

2. An HR specialist did a research on workers who stayed with the company and succeeded. When he discovers that they have a post-graduation degree from a certain place, he chooses to hire people with a postgraduate degree from the same location.

 

3.  A content marketing specialist found that when he develops material in the form of videos rather than photographs and blogs, he receives more views. In order to acquire more views, he is now creating additional material in the form of a video.

 

4.  An employee arrives at work at 8:30 a.m. every day and has never been late for work. As a result, she continued to leave for work at 8:30 a.m. in order to never be late.

 

Types of Inductive Reasoning

 

The different types of inductive reasoning.is based on the method of defining the sample from the population, and also on the methods of collecting the premise to arrive at a particular conclusion. The types of inductive reasoning  are as follows.

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Types of Inductive Reasoning

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1. Inductive Generalization

 

Based on the observations of the sample, a wider conclusion about the population is reached. The sample is used to form the premise, and the population is used to form the conclusion. The generalization form of inductive reasoning is determined by the sample size, population size, and how well the sample reflects the population.

 

As an example, if three out of four students can communicate in English, it is commonly assumed that 75 percent of the public can communicate in English.

 

2. Statistical Generalization

 

The inductive reasoning produces a conclusion about the population based on the inference established from the statistical validated sample. The population is statistically represented by the sample. 

 

The result from statistical generalization is more trustworthy as the sample is a proper representation of the population. Because the statistical sample is typically random and big, it provides the most trustworthy conclusion about the population.

 

3. Anecdotal Generalization

 

The anecdotal generalization draws a conclusion about a population from a non-statistical sample. The population is concluded based on the general characteristics of the sample. 

 

The performance of a school's students in a series of eight football matches is evaluated, and the kids are deemed to be the top football players in town.Because it makes a quick generalization about the population, the inference is less trustworthy than a statistical generalization.

 

4. Prediction

 

Based on the present or previous sample, this type of inductive reasoning predicts the future. The premise for this inductive prediction is derived from instances or phenomena. 

 

Rather than making a broad forecast, inductive reasoning provides a precise assertion about the likelihood of a future occurrence occurring, which is related to a current or previous case. These conclusions are time-specific, with the same sample and population in the current or previous occurrence.

 

5. Inference Based on Past Events 

 

From the name, it is clear that this type of inductive reasoning establishes a premise based on past events in order to predict the future. This inference uses a time-bound and historic sample to make a generalized prediction about the population and the future.

 

6. Inference Based on Current Events

 

Inference from present occurrences is analogous to inference from previous events. Based on the present sample set of examples or phenomena, inference based on current occurrences draws inferences about the future. 

 

This inference is slightly more trustworthy than the one based on previous events. The prediction of the weather based on current weather sample points is more reliable. 

 

7. Statistical Syllogism

 

A statistical syllogism uses a group generalization to get a conclusion about an individual. This population property A is generalized, and another member of the group is assumed to have property A. For instance,  The fact that 90% of snakes are harmless leads to the conclusion that a specific species of snake is harmless.

 

8. Casual Reference 

 

In this case, a casual relationship is created between the sample and the population. In Causal Inference, the validity of the findings regarding the population is quite low. 

 

The link between two samples collected from separate populations is based on a very casual association, and the actual relationship between the two populations can only be validated after extensive analysis.

 

Also Read | Probability Distribution Function

 

Inductive Vs Deductive Reasoning

 

Inductive and deductive thinking are fundamentally diametrically opposed approaches to reaching a conclusion or proposition. 

 

1. The primary distinction between inductive and deductive reasoning is that inductive reasoning begins with an observation, is supported by patterns, and then leads to a hypothesis or theory, whereas deductive reasoning begins with a theory, is supported by observations, and eventually leads to confirmation. 

 

2. Inductive reasoning assists you in transforming these observations into a hypothesis. So you start with some more particular knowledge (what you've seen/heard) and use it to develop a more broad hypothesis about how things work.

 

Deductive thinking is based on facts and rules, whereas inductive reasoning is based on patterns and trends. Deductive reasoning runs from general to particular, whereas inductive reasoning flows from specific to general. 

 

3. When seeking to understand how something works by spotting patterns, you may employ inductive reasoning. When identifying and constructing relationships between two or more entities, deductive reasoning may be more useful.

 

Some people refer to this as a "top down" strategy, in which you start at the top with your theory and work your way down to the bottom/specifics. I believe it's helpful to think of this as "reductive" reasoning — you're distilling your theories and hypotheses into specific conclusions.

 

 

Pros vs Cons of Inductive Reasoning

 

There are several sorts of reasoning, two of which are particularly prevalent and popular. There are two types of reasoning: inductive reasoning and deductive reasoning. 

 

Author Arthur Conan Doyle popularized the latter with his legendary investigator Sherlock Holmes, who employed deductive reasoning to solve murders or at least advance his inquiry. In many respects, deductive reasoning is the polar opposite.

 

Deductive Reasoning allows you to start with a group of observations and then infer the many situations or break them down to get at a single observation, which leads you to a conclusion after considering the numerous alternatives. 

 

Inductive reasoning allows you to make an observation and then apply it to a variety of similar and sometimes unlike instances. Listed below are some major pros and cons of Inductive Reasoning :- 

 

Pros :

 

1. Gamut of Probabilities

 

The most significant advantage of inductive reasoning is that it allows you to work with probability. Not all possibilities will be accurate or even conceivable, but you will have several choices. When you need to measure a concept or construct a view with very little material at hand, such as observations or experience, a starting point is required. 

 

Inductive reasoning leads you to that place. People from all sectors of life employ inductive reasoning both consciously and unconsciously. We prefer to utilize inductive reasoning to appraise others, from friends to peers. 

 

From professional problems to household duties, we use inductive reasoning to shape our beliefs, which determines how we approach these activities.

 

2. Encourages additional exploration

 

Inductive reasoning starts with an observation or inference. It encourages more investigation to see if the judgment or likely conclusion is correct or incorrect. During the process, anyone who employs inductive reasoning will investigate the provided context, the realm, and try or test several situations. 

 

This type of exploration is beneficial not just for investigating or analyzing probability, but it also assists the individual engaging in inductive reasoning in understanding how correct or erroneous the original evaluations and assumptions were.

 

Cons

 

1. Inferences are limited in scope and are inaccurate

 

Inductive reasoning has several limitations. It all starts with a single observation or conclusion derived from extremely specific and similar instances. In a varied society, this cannot possibly lead to a fair judgment or valid inference. 

 

Deductive reasoning collects observations before becoming particular, and even then it might go wrong at times. Inductive reasoning starts with something specific and then attempts to generalize, which will fail more frequently than frequency.

 

Also Read | Different Types of Research Methods

 

It can be concluded that Inductive reasoning is the ubiquitous mental activity of using existing knowledge to generate new knowledge that is likely, though not guaranteed, to be true. Inductive reasoning is required whenever people need to fill in gaps in their knowledge with “best guesses” about the state of the world. 

 

Generalizing that all snakes are black after encountering three black snakes, predicting rain in the afternoon upon seeing dark clouds in the morning, and using the analogy that an atom is like the solar system to infer new properties of atoms are all examples of inductive reasoning.