Research Writing

What is Inductive method characteristics types and examples

The inductive method is a way of reasoning to reach conclusions that start from the most specific and go to the broadest generalizations and theories. It starts with specific observations and measures to reach general conclusions.

The inductive method consists of three stages: observation, capture/observation of a pattern and development of a theory. For example, dogs are observed (observation), everyone is seen wagging their tails (default), all the dogs in the world are wagging their tails (theory).

Inductive reasoning is reasoning in which premises are seen as a way of providing strong evidence for the truth of a conclusion. While the conclusion of an inductive argument is certain, the truth of that conclusion in an inductive argument is likely, based on the evidence provided.

The inductive method can be defined by many sources as one in which general principles are derived from specific observations.

In this method, broad generalizations are made from specific observations, so it can be said that it goes from the specific to the general. Many observations are made, a pattern is noticed, a generalization is made, and an explanation or theory is inferred.

This method is also used in the scientific method; scientists use it to form hypotheses and theories. Deductive reasoning allows you to apply theories or assumptions to specific situations. An example of deductive reasoning might be:

All known biological life forms depend on liquid water to exist. Therefore, if we discover a new form of biological life, it will depend on the existence of liquid water.

This argument could be made every time a biological life form was found and it would be correct. However, it would be possible that, in the future, a biological life form will be found that does not require liquid water.

Types of inductive reasoning

– Generalization

Generalization derives from a premise about a sample from which a conclusion about a population is reached.

For example, let’s say there are 20 balls, which can be white or black, in a jar. To estimate their number, a sample of four balls is drawn – three are black and one is white. If we use inductive generalization, it can be concluded that there are 15 black and 5 white balls in the jar.

This assumption is biased as a small sample is being drawn from a larger population.

Examples of generalization

• I visited Scotland and didn’t like it. I sure as hell don’t like the rest of the UK.
• I met a rich woman, she is quite shallow. Surely all rich women are shallow.
• Yesterday, Juan met his sister-in-law and didn’t like him. Surely he won’t like his girlfriend’s entire family.
• I read a book by Mario Benedetti that I loved. I’m going to buy all of his books because I’m sure you’ll love them.
• Andrés lives in a poor neighborhood and is very happy. This means that all the people who live in poor neighborhoods are very happy.
• Yesterday I met a very interesting blue-eyed woman. I think all blue-eyed women must be pretty interesting.
• Several Muslims have been found in France who are religious fanatics. Therefore, all Muslims must be religious fanatics.

– Statistical syllogism

The statistical syllogism originates from a generalization to a conclusion about an individual. For example:

• A proportion Q of the population P has an attribute A.
• An individual X is a member of P.

Therefore, there is a probability corresponding to Q that X has A.

Examples of statistical syllogism

1. Most farm workers have the flu.
2. Juan is an agricultural worker.
3. Juan is likely to catch the flu.
1. No woman can breathe underwater.
2. Divers breathe underwater.
3. No diver is a woman.
1. All cats sleep.
2. All men sleep.
3. All men are cats.
1. 50% of philosophers are Greek.
2. Emiliano was a philosopher.
3. There is a 50% chance that Emiliano is Greek.
1. People usually eat chocolate ice cream.
2. I am a person.
3. I usually eat chocolate ice cream.
1. Girls play with dolls in the school yard.
2. my daughter is a girl
3. My daughter is going to play with dolls in the backyard.

– Simple induction

It comes from a small sample premise to a conclusion about another individual:

• A proportion Q of the known population P has an attribute A.
• Individual I is a member of P.

So there is a probability corresponding to Q that I have A.

Simple examples of induction

• Yesterday my brother came to visit me and my father bought ham. Today my brother came to visit me and my father bought chorizo. So if my brother comes to visit tomorrow, my father will buy some sausage.
• My mom gave me a pair of earrings and I lost one. My cousin gave me another pair of earrings and I lost one. My boyfriend gave me a few more earrings and I lost one. I suggest that every time I get a pair of earrings, I lose one.
• Yesterday they visited us and my mother cleaned the room. Today comes another visit and my mother is cleaning again. This means that whenever he comes to visit the house, my mother cleans the room.
• On Monday, Andrea didn’t have to work and woke up late. Yesterday, he had the day off and woke up late. On Sunday, he also didn’t have to work and woke up late again. I suggest that on days when Andrea doesn’t have to go to work, she wakes up late.

– Argument from analogy

This process involves taking into account the shared properties of one or more things and then inferring that they also share other properties. So:

• P and Q are similar with respect to properties a, b and c.
• Object P was found to have a property x.
• So Q probably also has the property x.

Examples of argument from analogy

• Horseshoe is a horse that shoes for humans.
• Wool is to the sheep, which is milk to the cow.
• A driver is a bus, what a pilot is an airplane.
• The radio is for listening, as the newspaper is for reading.
• Sleep to sleep, as hunger is to eat.
• Tears are sadness, laughter is joy.
• To lie down is to lie down, as sitting is to lie down.
• Cold is hot, as darkness is light.
• A bee is a hive, as an ant is a colony.
• France is for wine, Colombia is for coffee.
• Fin is a dolphin, which hand is human.
• Colombia is to Bogotá, as Argentina is to Buenos Aires.
• Soap is clean, as dirt is dirt.
• Gloves are on the hands, like socks on the feet.

– Casual inference

A casual inference draws a conclusion about a causal connection based on the conditions for the existence of an effect.

Assumptions about the correlation of two things may indicate a causal relationship between them, but other factors must be established to be confirmed.

Examples of causal inference

• An investigation carried out in several schools in Spain found that the students who obtained the best grades in computer science were of Moroccan origin. Thus, it was concluded that Moroccan origin was a causal factor in obtaining better computer science certificates.
• In an investigation of alcoholism, it is observed that the five subjects of the study have very different life circumstances. However, they all watched as their parents or step-parents repeatedly drank in front of them. For this reason, the researchers conclude that seeing the father figure drinking frequently is a causal factor in alcoholism in adult men.
• A study on fidelity between couples looked at ten couples (including homosexuals and heterosexuals) with different backgrounds and life histories. Some individuals in the study grew up in the homes of divorced parents or witnessed their infidelity. Those who had been unfaithful to their partner had grown up in homes where infidelity had no place. The study concluded that seeing parental infidelity is not a causal factor of infidelity in children.

– prediction

A conclusion about an individual’s future is reached from a past sample.

Examples of forecast

1. Every time Juan gets together with his family, he has fun.
2. Juan will be reunited with his family today
3. So it will be a great time.
1. Healthcare personnel are contracting a very contagious flu.
2. My girlfriend is a nurse.
3. So I’m going to get the flu.
1. Hannah was unfaithful to her husband when he was traveling.
2. Ana’s husband is traveling.
3. For this reason, Ana will be unfaithful to him.
1. When I went to Paris, I thought it was beautiful.
2. Tomorrow I’m going to Paris.
3. It will look nice to me.
1. My brother invested in stocks and made a lot of money.
2. Today I’m going to invest in stocks.
3. Consequently, I will earn a lot of money.
1. When I go to this restaurant, at most.
2. Tomorrow we’re going to that restaurant.
3. I will eat a lot

Differences with the deductive method

In a deduction, you start with a general argument or hypothesis and examine the possibilities for reaching a specific, logical conclusion. The scientific method uses deduction to test hypotheses and theories.

An example of a deductive argument is as follows:

• All men are mortal.
• Individual x is a man.

Therefore, individual x is mortal.

The main difference between the two methods is the research approach. While the deductive method is geared towards testing theories, the inductive method is geared more towards creating new theories that emerge from data or information.

Generally, the inductive method is associated with qualitative information, as it is generally subject to subjectivity, it is more open, it is inductive, it is more process-oriented, it is comparative and the description is narrative.

In turn, the deductive method is usually associated with quantitative research methods, such as deduction, objectivity, numerical estimation and statistical interference. It is also generally more results-oriented.