Before making a decision, you typically think things through from the first step to the expected outcome.
We sometimes make decisions based on our current situations or environments. It only makes sense that if it’s windy or stormy, you’d bring a jacket with you before stepping outside. This is because previous similar scenarios have proven that you’d need a jacket in those types of weather conditions.
This is one logical exercise we all practice daily, even when we’re not aware of it. We take into consideration small things to draw up a conclusion that influences our decisions. This is known as inductive reasoning. It also plays a significant role in writing, and there’s more to this than what most people probably know.
So, if you’re wondering what inductive reasoning is, how it works, how we use it every day, and the different types, then it’s time to find out more, starting with…
- What Is Inductive Reasoning?
- Inductive Reasoning In Research
- What Is Inductive Reasoning? – The Different Types
- How Is Inductive Reasoning Different From Deductive Reasoning?
- How Inductive Reasoning Works
- Additional Info On Inductive Reasoning
- What Is Inductive Reasoning? – Final Thoughts
What Is Inductive Reasoning?
Inductive reasoning is a method that we use to draw conclusions. These can be assumptions based on previous experiences. This form of reasoning is also called inductive logic or bottom-up reasoning.
How It’s Used
It’s mainly used in three ways. We use it when we try to make logical decisions almost every day. It helps us to navigate our way through the day and to understand the world. We also use it academically. While conclusions differ in almost every situation, inductive reasoning is applied in our academic lives.
Lastly, it’s used for research and science purposes. Scientists and researchers gather data through experiments and observations. It helps them to further test theories after getting an inductive inference.
Read more: How To Calculate Probability
Inductive Reasoning In Research
Not only is inductive reasoning used informally in everyday situations, but it’s an important element in research. When you conduct research, you make observations or gather data first. Then, you broadly view your data and search patterns. Lastly, you make general conclusions from the patterns, and you incorporate the conclusions into theories.
Most researchers use inductive reasoning when they’re conducting qualitative research. It can still be applied when conducting quantitative research too. As a researcher, you might need a refresher course before conducting any research. Have a look at the 5th edition of Research Design: Qualitative, Quantitative, and Mixed Methods Approaches.
An Example of Inductive Reasoning in Research
An easy example of how to use inductive reasoning in research is when you conduct exploratory research on behavior. You explore how children born with guardians who work in office set-ups are different from toddlers born with parents who work from home.
You start by distributing a survey to parents. Ask them about the behavioral differences between their children. Compare children’s behavior when one has been raised while parents worked away from home and the other had parents working remotely. This data becomes your observation.
Look for the pattern…
Analyze it by categorizing the responses so that you can identify repeated themes, similarities, and differences. This analysis will show you a pattern: children raised while guardians work away from home did not communicate as effectively as those raised with guardians who work remotely.
Based on these results, you can conclude that children’s behavioral traits were partially shaped by their guardians’ presence or absence. This generalization can be used to further test research questions.
What Is Inductive Reasoning? – The Different Types
There are many types of inductive reasoning, all serving different purposes formally or informally. So, let’s take a look at some of the most commonly used ones. Who knows, you might identify the one you relate to the most in your everyday life.
This form of induction depends on a sample. The downside to this is that a random sample isn’t always accurate. For example, you might observe a group of flamingos and state that all flamingos are pink (premises); therefore, all flamingos are pink (conclusion).
This conclusion is, in fact, not true because some flamingos are more orange or red, and others are pure white. Flamingo habitats and food sources vary from place to place. So, the conclusion from inductive generalization can be stated as being a weak argument.
Strengthen your argument…
There are other ways to strengthen your argument when using an inductive generalization. You can evaluate your data using a large sample instead of a random one. You can also opt for counterevidence to come up with your conclusion.
Statistical and Bayesian Generalization
Specific numbers are used to make statements, mostly about populations. Non-statistical generalizations aren’t as specific, and it’s safe to say that they aren’t as popular either. By using statistics for this generalization, it becomes quantifiable, and the conclusions are stronger.
A simple example is “90% of the flamingos I’ve seen during my gap year are pink.” Statistics validate your conclusion and make your argument more concrete. If you’re an admirer of flamingos by any chance, get this large inflatable pool floating flamingo with durable handles. It’s perfect for summers at the beach or swimming pool.
Consider new data…
Bayesian generalization is an adaptation of statistical reasoning where you consider new or additional data. For example, local data will allow for a more precise estimate of the percentage of pink flamingos.
This means that you make a cause-and-effect link between different things. Two main things influence good reasoning. These are direction and strength. The direction in which your conclusion is headed should be clear based on your observations. There should also be a strong relationship between the cause and effect.
It involves making a correlational connection between different things. One event may act as a sign that another event will occur at a given time. For example, “The cloudy sky and wind are a sign that it might rain later today.”
This reasoning is based on the similarities things may have. First, you link two things together and then conclude that the attributes of one thing must be true for the other thing. You have a strong conclusion if you use a literal comparison; therefore, analogical reasoning is also called comparison reasoning.
How Is Inductive Reasoning Different From Deductive Reasoning?
Inductive reasoning is often confused with deductive reasoning. It draws conclusions by going from specific to general. The exact opposite can be said about deductive reasoning, which goes from general to specific conclusions.
While inductive is a bottom-up approach, deductive reasoning is a top-down approach. It means that deductive reasoning starts with a theory that could develop into a hypothesis. It mostly produces rock-solid conclusions, but this form of thinking is only useful in limited circumstances. Then you test it empirically. An example of deductive reasoning is :
“All insects have six legs and two antennae. Therefore, beetles have six legs.”
How Inductive Reasoning Works
It is an analytical soft skill. A soft skill doesn’t require formal training. It relates to how you interact with people, ideas, and social interactions. Inductive reasoning is a good skill to have when you’re in the workplace. You can use it to develop strategies, policies, and plans. If you must, it would be worth mentioning having this skill in your job applications and interviews.
Examples of Inductive Reasoning
Here are a few examples, and there’s a mix of the different types that were mentioned above. See if you can also identify them.
- Bonny always leaves for work at 06:45 a.m. She is always on time. She assumes that if she leaves for work at 06:45 a.m. tomorrow, she’ll be on time.
- The picture frame in the sitting room is green, and so is the one in the kitchen. The ones in the hallway are also green. Therefore, all the picture frames in the house are green.
- Erik is showing his friend Elson a diamond ring he bought. Erik has told Elson that he’s planning to marry Julia. He must be surprising Julia with the ring tonight.
- Every time Cleo eats fish, her face swells up. She must be allergic to it.
- Leroy is a good basketball player. His family has a basketball court in the back, so his sisters must be excellent basketball players too.
Requirements to Develop Your Inductive Reasoning Skills
Since inductive reasoning is about observations and drawing conclusions, you can use this skill to make predictions and create generalizations. If you want to develop or improve your reasoning skills, focus on the following points:
- Pay attention to detail: be more conscious and aware of your surroundings. Taking in different details about places and things will help when it’s time to analyze a given scenario.
- Recognize patterns: Once you can recognize patterns quickly, you can draw a possible conclusion.
- Make projections: It means that you learn to make use of the information that you already have to predict a future outcome. This is common in the academic field, where educators can conclude what grade a student will get before taking a test. This also comes in handy for those in the financial or marketing field since financial projections are well-known.
- Use Emotional Intelligence (EI): This is the ability to perceive people’s emotions. People with high EI are more understanding.
- Memory retention: Work on retaining information as accurately as possible. Some predictions are based on previous scenarios and outcomes. You can take down notes to help you improve your retention skill.
Additional Info On Inductive Reasoning
Let’s start with the statistical approach, check out the Mathematical Theory of Bayesian Statistics, the Statistical Learning with Sparsity (Chapman & Hall/CRC Monographs on Statistics and Applied Probability), and the Rethinking the Foundations of Statistics (Cambridge Studies in Probability, Induction and Decision Theory).
In addition, we also fund the Geometry of Quantum States: An Introduction to Quantum Entanglement, as well as the Linear Models and Generalizations: Least Squares and Alternatives (Springer Series in Statistics), available online in 2023.
Lastly, in regards to causal reasoning, why not try The Oxford Handbook of Causal Reasoning (Oxford Library of Psychology), the Causal Reasoning in Physics, or how about the Book of Why, along with Thinking and Reasoning: An Introduction to the Psychology of Reason, Judgment and Decision Making.
What Is Inductive Reasoning? – Final Thoughts
Inductive reasoning is a way of thinking logically. It involves forming generalizations based on observations, experiences, and facts.
There are different types of inductive reasoning, and this skill is used in our daily lives, research, and academic life. Work on developing this soft skill because it will help you on your career path to focus on details, memory retention, and recognizing patterns.
There is a notable difference between inductive and deductive reasoning, even though the two are easily confused.
Good luck, and enjoy your reasoning!