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Deductive vs Inductive Reasoning


Vishwadeep Khatri
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Message added by Mayank Gupta,

Deductive Reasoning is a logical thinking approach that works from general to specific. Works from theory > specific hypothesis > collect observations > conclusion. It is also known as top-down approach.

 

Inductive Reasoning is a logical thinking approach that works from specific to general. Works from specific observation > detect pattern > formulate hypothesis > theory. It is also known as bottom-up approach.

 

An application-oriented question on the topic along with responses can be seen below. The best answer was provided by Johanan Collins on 17th Aug 2021.

 

Applause for all the respondents - Shrikant Angre, Somnath Mukhopadhyay, Amit Kumar Singh, Abhishek Chaudhary, Johanan Collins, Vinod Jeba Azir, Darryl Collins.

Question

Q 391. What is the difference between Deductive Reasoning and Inductive Reasoning? Compare and contrast using examples. How are these used in the Lean Six Sigma world?

 

Note for website visitors - Two questions are asked every week on this platform. One on Tuesday and the other on Friday.

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Deductive reasoning is a scientific method that uses deduction to check or test theories and hypothesis.

 

Deductive reasoning consists of three steps, premise one, premise two and an inference. For Example, Premise one is all men are mortal, premise two is Sampson is a man. Thus, we infer that Sampson is a mortal.

 

Deductive Reasoning is the foundation of research and academic research in specific. In academic research we first make claims, gather data, and then test the claims or to be specific the hypothesis.

 

Inductive Reasoning makes broad claims about an observation. Data is gathered and then conclusions are drawn making it opposite to deductive reasoning.

 

The main difference between the two forms of reasoning is that deductive makes claims based on theory while inductive makes claims based on observations.

 

The main way that the two are used in the Lean six sigma world is inductive reasoning is used in Gemba walks and “management by walking around”, where the practitioner is observing the processes and then making decisions. While the entire DMAIC process under six sigma would be grouped under deductive reasoning as the practitioner theorizes a result, gathers data and tests if their results hold true.

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  Deductive Reasoning Inductive Reasoning
Definition It takes general rule and then uses it to make specific observation It uses specific observations or examples and then applies it to make a general rule
Basis of reasoning It uses facts, definitions to arrive at a conclusion It takes into account patterns found to arrive at a conclusion
How it is done? Start with a theory/Hypothesis
Do a Quantitative research to test the Hypothesis
Then confirm it to drive reasoning
Start with a data at hand
Do inferential statistics and try to draw inferences
Thus, end up doing Qualitative research
Limitations Conclusions drawn will be true, if we are very clear and particular about the sample and the type of the sample we are driving conclusion on Conclusions drawn, it is very difficult to prove them
Example Existing theory: There is always a delay in Low cost airlines
Building a hypothesis: If the passenger fly with low cost airline, then there will be a delay
Data Collection: Collect the real time data
Analysis and reasoning: Analyze the results to accept or reject the hypothesis
Observation:  A low-cost airline flight is delayed
Observing a pattern: Another 30 flights from low-cost airlines are delayed
Develop a theory: There is always a delay in Low cost airlines
Application This is generally used in research industry to identify the root causes and make remedies basis the outcome of the study done This is generally used in predictive analytics, thus to predict the trend or in current scenario (how covid-19 will spread etc)

 

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Inductive reasoning is – when we use specific scenarios and make generalized conclusions out of them. This is also called as cause and effect reasoning. Inductive reasoning can also be considered as a “bottom up” approach. For example, one might observe that his friend is good at studies, his friend’s older sister is good at studies and his mom’s older sister is good at studies. Inductive reasoning would conclude that - all older sisters are good at studies.

 

Deductive reasoning is – when we make a generalized statement and back it up with specific scenarios/ information. It can be conceptualized as a “top down” approach while drawing conclusions. For example, think of a statement that - all mangoes are fruits. When you bring-up specific information like “all fruits grow on trees”, then we can deduce that all mangoes grow on trees.
Inductive and deductive reasoning are crucial when we collaborate in the workplace. We keep on making inferences and bring conclusions using both the methods to make any kind of decision, generate ideas and improve processes. 

 

Examples - Inductive reasoning:
•    Determining when one should leave for work following traffic patterns
•    Deploying a new accounting process following the way users interact with that particular software
•    Deciding on bonus plans basis outcome of employee survey
•    Changing time for a training session or approach based on participant energy levels

 

Examples - Deductive reasoning:
•    Developing a training pitch plan that can be effective for a specific audience
•    Designing the building plan of a mall and layout of shops to maximize sales
•    Planning out a budget and investment pattern to get the highest yield from investments
•    Determining the most efficient ways to get VOC from clients
 

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Deductive Reasoning:

Deductive Reasoning is the reasoning of one or more general/logical statements or hypothesis statements to get one final logical conclusion. Deductive reasoning is also called Top Down reasoning.

A simple example of deductive reasoning is:

  1. If X=Y
  2. And Y=2
  3. Then X=2

Or

  1. All the participants of Six Sigma Black Belt course are Six Sigma Green Belt certified.
  2. Aman and Akash are participating in Six Sigma Black Belt course.
  3. Therefore, Aman and Akash are Six Sigma Green Belt certified.

Inductive Reasoning:

Inductive Reasoning is the reasoning of combining observations and information drown from the experience or a set of data to get a generalize conclusion.

A simple example of Inductive Reasoning is:

  1. Every time when it rains, wind blows from the East.
  2. Today wind is blowing from East.
  3. Therefore, it will rain today.

Deductive Reasoning vs. Inductive Reasoning:

The basic difference between deductive reasoning and inductive reasoning is that deductive reasoning starts with a general statement and finds the possibility of reaching to a logical conclusion while inductive reasoning, in place of finding logical conclusion, makes broad generalization from the specific observations. We can say that deductive reasoning generates specific conclusion from the general statements while inductive reasoning generates generalize conclusion from the specific statements.

 

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Use in Lean Six Sigma:  

The deductive reasoning moves towards the hypothesis testing and used to analyze theories that are already exist. Deductive reasoning can make analysis simpler, faster and more reliable. Deductive reasoning can also be used in problem solving, better team work and effective customer services by analysing the facts or the information and finding the real problem and logical reasons for that to get effective solutions.

While inductive reasoning can be used to make the data collection plan and analyze the collected data to establish any pattern or the relation.

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DEDUCTIVE REASONING & INDUCTIVE REASONING

There are two main types of reasoning used in developing and testing scientific theories or argument namely Deductive & Inductive reasoning. In Scientific circle, one can does not prove a hypothesis being true, but they can collect evidence that points to it being true. There is only conclusion drawn from facts and observations. Just like lawyers can not prove their theory being true but they can provide evidence that points to it.  

There is also a third theory called abductive theory, but we will discuss Deductive and Inductive Theory.

 

INDUCTIVE THEORY

Inductive theory works from specific observations to a generalized conclusion or theory. It is common to conduct inductive research when there is very less or no existing theories on the topic. When you don’t know much about the topic you observe and note the observation. Begin noticing patterns and regularities, then formulate some hypothesis that can be explored and finally developing the general theory. Because of this approach being started from micro level observation and formulating the general theory at the end also called “Bottom UP” Approach.

Giving all of you a Pop culture example the fictional character Sherlock Holmes is a master of Inductive reasoning. He is masterful observer who observers all the details carefully to reach to the most likely conclusion in those circumstances.

 

induct.gif.a4fc42c2f6b739a513c2d203c630236b.gif

 

 

a.      Observation

-        A low-cost AC has failed the ambient test after running for 20 hours.

-        Swan A is white

b.      Observing a Pattern

-        10 more low- cost ACs have failed the ambient test after running for 20 hours.

-        Swan B & C are also White

c.      Developing Theory

-        Low-cost ACs will always fail the ambient test after running for 20 hours.

-        All Swans are white

 

Limitation of Inductive Theory:

An Inductive theory can not be proven, it can be invalidated, however.

You observe 150 more low-cost ACs fail the same test so that validates your theory but you can never prove that 151st AC will also fail. But the larger the dataset the more reliable it is. A conclusion can seem to be true at one point until further evidence emerges and a hypothesis must be adjusted.

 

 

A CONCLUSION IS EITHER WEAK OR STRONG, NOT RIGHT OR WRONG.

Everyday inductive reasoning is not correct always but often useful. An Example of this would be A farmer feeds a turkey every day, so the turkey assumes that the farmer cares for its wellbeing. Only when Thanksgiving rolls around does that assumption prove incorrect.

 

 

DEDUCTIVE THEORY

Deductive theory works from top to bottom and that is why it called “Top Down” approach. It works from more general to more specific. In this an already existing theory is tested by narrowing it down to more specific hypothesis that we can test. Then the hypothesis is narrowed down further when we collect observation to validate or invalidate the hypothesis. This will proceed to us being able to test the hypothesis with specific data which can either confirm or deny the theory so that it can be adjusted or changed.

 

deduct.gif.f31fc56cd97a8455141887ab17b71329.gif

 

 

a.      Predefined Theory

-        All low cost ACs fail in ambient test after 2 hours of running

-        All swans are white

 

b.      Formulate A Hypothesis

-        If we buy low-cost AC then it will fail in ambient test

-        If we find a swan, then it will be white.

 

c.      Collect data to validate the hypothesis

-        Collect data for 1000 more low-cost ACs

-        Check 500 swans

 

d.      Analyze the result

-        2 out of 1000 ACs run do not fail in Ambient test if run for more than 2 hours (Reject or Adjust the theory)

-        All of 500 swans are white (Support the theory)

 

Limitation of Deductive Theory:

The conclusion based on deductive reasoning can only be true if all the premises set in Inductive reasoning are true and terms are clear.

Example

  • All dogs have fleas (premise)
  • Benno is a dog (premise)
  • Benno has fleas (conclusion)

Based on the premises we have; the conclusion must be true. However, if the first premise turns out to be false, the conclusion that Benno has fleas cannot be relied upon.

Also, we should be very careful of deductive reasoning that appears to make sense without pointing to a truth. Someone could say “A dog has four paws. My pet has four paws. Therefore, my pet is a dog.” The conclusion sounds logical but isn’t because the initial premise is too specific.

 

Combining Both Type of Reasoning

The two methods are very different when conducting research. Inductive reasoning is more open ended and exploratory, while deductive reasoning is specific in nature. Both theories are combined in science to reach more and more close to the truth. It is a cyclical process. Inductive research is followed up with deductive research to confirm or validate the theory if not validated then it can be adjusted. Again, adjusted theory can be validated again by using deductive reasoning and the cycle goes on.

 

Using In Lean Six Sigma Word

Both type of reasoning is used in Lean Six Sigma word. Most hypothesis testing that are done in analyze phase are based on this reasoning. If our hypothesis is true, we accept the root cause which was our initial theory otherwise we look for more factors.

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There are many tools that we can use to make critical decisions. Reasoning is one among the several tools that often appears naturally which includes inductive, deductive, and abductive methods. 

Deductive Reasoning:

Deductive reasoning a.k.a deductive logic a.k.a top-down reasoning is a process of arriving at a logical conclusion based on the statements (premise) that are generally assumed to be true. Deductive reasoning Starts with a general rule (a premise) that we know to be true. From that general rule, we make a true conclusion about something specific. In other words, it is a logical reasoning process from known facts to conclusions.

Example: All men are mortal. Jim is a man. Therefore, Jim is mortal. Here if the first two statements (premise) are true then the conclusion must be true as well.

image.png

 

 

Inductive Reasoning:

Inductive reasoning approach is right the opposite of deductive reasoning. Here generalized information is gathered first from specific scenarios to come to a conclusion. In other words, in this approach, you gather data, and then determine what logical conclusions or theories could be derived from that data.

Example: All senior supervisors in my company have university degrees. Therefore, you must have a university degree to become a senior supervisor.

image.png

 

 

 

Difference between deductive and inductive reasoning:

 

 
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Deductive Reasoning

Inductive Reasoning

Direction

Top-down

Bottom-up

Premise

Specified as facts or general principles (it is warm in the summer in Chennai)

Based on observations of specific cases (All crows Jim has seen are black)

Conclusion

Conclusion is more special than the information the premise provides. Conclusions are reached by applying logical rules to the premises directly.

Conclusion is more general than the information provided by the premise. Conclusion is reached by generalizing the information of premises.

Validity

If the premises are true, the conclusion has to be (MUST) be true.

If the premises are true, then the conclusion is probably true.

Usage

More difficult to use (mainly in logical problems). Requires facts which are definitely true.

Used often in everyday life (fast and easy). Evidence is used instead of provided facts.

 

Use of deductive and inductive reasoning in lean six sigma world:

Though lean six sigma approach relies on various tools for systematic problem solving, the art of critical / scientific thinking is imperative to its success. Tools cannot by any means substitute reasoning characteristic.

Both the methods can be applied effectively in problem solving. The theory of inventive problem solving (TRIZ), enables one to take a logical, structured and systematic approach in evaluating a problem, identifying contradictions and arriving at innovative solutions. Addressing contradictions requires deductive / inductive reasoning. Sometimes, we move from a specific problem to a generic problem which is inductive in nature and from the generic problem to generic solution and return to a specific solution which is deductive in nature.

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Deductive Reasoning. California State University defines deductive reasoning as “draws specific conclusions from general principles or premises”. Valid reasoning is at the heart of deductive reasoning.


Inductive Reasoning. Inductive reasoning as defined by Utah State University, starts from observations or data and makes broad generalizations from specific observations.
 

Inductive reasoning can have some uncertainty, whereas provided that the premises are true, the conclusions reached by deductive reason have no uncertainty in them. Inductive reasoning is used to formulate hypothesis and deductive reasoning is used to apply them to specific application areas.


Inductive and Deductive Reasoning in Lean Six Sigma.


Inductive Reasoning. The very philosophy of Lean is inductive thinking. Since Inductive reasoning is from observation to generalization, it has found a smooth adaptation in lean thinking. For example, the Gemba walk could be the start of an observational study by managers or supervisors which could lead to change. Similarly, Inductive thinking also contributes in a very big way to the Kaizen approach to continuous improvement.


Deductive Reasoning. Deductive reasoning is the drawing of specific principles from general observations. Moving from a push system to a pull and continuous flow would not have been thought possible in the past. Observation of specific principles in nature such as how does an animal, say a lion provide for itself. Does it store food? (Nil Inventory or Just in Time). Does it kill more than that it requires? (Over Production). Does it waste food? The Lion is agile in the physical and mental area knowing the places where the prey is available. Similarly, businesses having knowledge of their suppliers and supply chains would reduce waste.


References
http://www.csun.edu/science/ref/reasoning/deductive_reasoning/index.html viewed on 16 Aug 2021
https://www.livescience.com/21569-deduction-vs-induction.html viewed on 16 Aug 2021

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