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Difference Between Deductive, Inductive and Abductive Research
Difference between Deductive, Inductive and Abductive Research
These three approaches tell us how we are treating data and theories.
In theoretical research, deduction, induction and abduction can be also known as modes of argumentation:
- Deduction: Data finding first to support an argument.
- Induction: From argument finding to explanation of data;
- Abduction: Supplying a permit or license that enables or allows us to move from data to argument.
Deductive and inductive approaches are the two methods which we use most of the times in research.
Top two reasoning’s: Deduction and Induction
•It is thought to be a search for how methodological or scientific hypotheses originate to be, over how we try to measure those in relation to their truth or falsity (see Hanson, 1958).
•There has been a discussion over whether such logics are possible or thinkable especially if they generate or form a unique/distinctive method for reasoning that varies from traditional Inductive and Deductive logic (Audi, 1999).
Deductive research goes from theories to data. Task is to find theories which are very well-known or generally defined and then apply them to a specific phenomenon. The collected data will then either approve or disapprove these theories which you have tried to apply; both of these outcomes will be then valuable. Quantitative research is most commonly linked or associated with Deductive approach.
Deductive approach declares to be the best and most common in practice. In this approach you highlight or outline an argument based on your existing knowledge about the selected subject or topic, then research on it to fill in the gaps. This is also called active reading.
Theory Hypothesis Observation Confirmation
- Deductive approach starts or works from more general to more specific.
- This type of research sometimes informally called a top down approach.
- Final results, which are conclusions follow logically from the provided initial premises.
- In deductive reasoning, arguments which are generally used are based on accepted principles, laws and rules.
- In this approach ‘effects’ are derived from ‘causes’.
- There are usually two variable in the research which are X and Y.
- It initiates or opens with an extensive explanation or the statements which are supposed to be factual/true and continues with predictions for defined and specific observations which are supporting it.
Certainty/guaranty of conclusion in deductive approach
Deductive research opens or starts with the declaration of a rule which is general and continues from there to certain, precise and specific outcome or conclusion. In deductive reasoning, if the starting declarations are factual/true, then the outcome result which is a conclusion must also be factual/true. For an instance we say that math is deductive:
- If x = 5
- And if y = 2
- Then 3x + y = 17
In this above mentioned example, it is a logical necessity or prerequisite that 3x + y = 17; 3x + y must equal 17. As a practical, formal, representative and symbolic deductive logic which uses a linguistic that looks like the math equation above, complete with its own language of syntax and operators.
- Premise one: if entropy which is a disorder in a system will grow or increase unless some energy is excluded or expended,
- Premise two: and if the system is my bedroom,
- Conclusion: the disorder will then grow or increase in my bedroom unless I clean or exclude it.
- In the syllogism mentioned above, the first two explained statements which are the premises or propositions, lead logically to the final and third statement which is the conclusion.
Deduction: empty reasoning
The syllogism which is explained above, in this form of research, the reason is empty. Its outcome or the conclusion can never explain or state more than which is already identified or known in all the premises; it can only make it clearer or explicit. Deductive research helps in the physical sciences because science has general laws unlike intelligence for example the law of gravity from which specific or particular types of info can be discovered.
Comparison of intelligence with deduction
Intelligence is not formed of general philosophies or principles with the clarifying power of laws of Newton. Intelligence can help or assist in creating or generating very new hypotheses, but analysts will most probably find very small or little value in deductive research to assist them to generate or produce some sort of reliable intelligence.
Comparison of truth against validity in deductive research
A conclusion is true (sound) or false (unsound), completely depends upon the truth or soundness of the original premises for that any of the premise is either true or false. Simultaneously, independent of the sound or unsoundness of the premises, the deductive inference (the process of joining the dots starting from the premise to conclusion) is either valid or invalid.
- All inferences are not of the same range or variety. For example take an example of the inference of
- “Adam is rich” from the conclusions
- “Adam lives in Kensington” is premise one
- “Most people living in Kensington are rich.” Is premise two
- In this example, the fact of the first sentence which is conclusion is not certain or guaranteed but it’s made likely just by the combined truth of the 2nd and 3rd sentences.
Induction, abduction and statistical data
When combined all the Inductive inferences they generate a fairly varied/heterogeneous class, but for the current or present purposes they are usually be considered as those inferences that are purely based on the statistical data, such as the experimented frequencies of occurrences of any type of the particular feature in a certain population. Following is an example of an inference:
- 96 per cent of the Flemish college students speak both Dutch and French.
- Louise is a Flemish college student.
- Hence, Louise speaks both Dutch and French.
However, the significant and relevant statistical information may also be more imprecisely described in the premise, “Most people living in Chelsea are rich.”
There is an argument related to the conclusion of an inductive research which can either be specified in a purely qualitative terms or a quantitative one. For instance, this argument has a probability of 96% that Louise speaks both languages Dutch and French or it can also sometimes be specified in qualitative terms; the probability that it is true is high enough and also sometimes not.
If we talk about the mere fact that statistical data is the one on which the interference is based on then it is not that enough to categorize it as an inductive one. One may also have observed white swans and no non-white swans and concluded from it that all the swans are white, because that would give the best explanation for why to observe so many white swans and no non-white swans. This would be considered as Abductive inference
InInductive approach you go for data first and then you try to formulate a theory. In this approach the better thing is that own theories can be formed but It’s much harder to manage and much harder from a methodological perspective. Inductive approaches the aim which is usually focused on exploring new phenomena or looking at previously researched phenomena from a different perspective. Qualitative research is most commonly linked or associated with Inductive approach.
Inductive approach is common but less effective when compared to deductive. In this approach you research the topic first and then argument comes up which is based on your research. This is also called reactive writing.
Observation Pattern Tentative Hypothesis Theory
- Inductive research works the other way, from specific to broader generalizations and theories.
- This type of research sometimes informally called a bottom up research.
- Conclusions are most likely based on premises.
- This type of research commonly involves some degree of uncertainty.
- Observations likely to be used for it.
- Inferring ‘effects’ from ‘causes’
- There are usually two variables in the research which are X and Y.
Inductive research starts with the findings which are very limited and specific in scope, and then continues to an outcome or conclusion which is generalized but not very certain in the light of collected data. In inductive approach the premises are there to support the result or conclusion but they do no ensure it. Therefore the conclusion is known as hypothesis.
Difference between Induction and Abduction
The best way to differentiate between induction and abduction is this:
- Both of them are ampliative, which means that the conclusion goes totally beyond what is basically contained in the researched premises.
- But in abduction there is an understood or clear appeal to descriptive reflections, whereas it’s not the same in induction. In induction there is only an appeal to experiential statistics. (“Only” is emphasized because there may also in abduction).
Induction as non-deductive reasoning
There are different types of arguments which can be classified in relation to their premises which provide:
- Conclusive support
- Partial support
- Or only the appearance of support(which is no real support at all)
When we talk about the premises which provide conclusive support to the conclusion, it means that if all the premises were true then it would be impossible for the argument conclusion to be false in any way possible. These arguments are called Deductive arguments. When we talk about the premises which provide partial support to the conclusion, it means that if all the premises were true then they would give us good reasons but not conclusive reasons for us to accept the conclusion. So we say that although all the premise are true and provide us with some sort of evidence to support the conclusion but the conclusion will still remain false. These arguments are called Inductive arguments. 
Abductive research starts with incomplete observations and continues to the closest possible explanation for it. Abductive research gains daily decision making which has the best information, but incomplete. A medical diagnosis is the best application of Abductive research. If there’s a set of symptoms, what diagnosis would explain them best? While in inductive reasoning there is a requirement that would explain the subject completely and fairly, weather positive or negative. In Abductive reasoning there is a lack of completeness, it can either be in the explanation or evidence or maybe both.
How does qualitative data become evidence?
- The difficult problem is the way to excellently represent the method by which data grows to become evidence.
- For example, from a medical angle, it’s been suggested that some form of “abduction” might be appropriate (Upshur, 1997).
- Abduction is believed to be a method of research in which the logic of discovery is highlighted over the logic of justification
Abduction and Creativity
In Abductive reasoning, the research may be revolutionary, intuitive, and creative. All the Einstein’s work was not either inductive or deductive; however it involved creative imagination or visualization that hardly seemed important to the observation of falling elevators and moving trains.
What kind of logic is Abduction?
- Abduction is a process of research in which the logic of creativity/justification is given more importance than the logic of justification.
- It is more like a process rather than a conclusion/outcome in hypothesis formation.
Abduction: term invented by Charles Peirce (1839-1914)
- It’s an Observation of an anomaly,
- Abduction of hypotheses is to explain the anomaly, inductive testing of the experimental hypothesis.
- Deductive confirmation that the chosen hypothesis forecasts the original anomaly (which is not an anomaly afterwards).
‘Inference to the Best Explanation’ (Lipton, 1993)-what does it mean?
X causes Y- (high rise and (causes) vandalism)
‘The most economical explanation’= design
So to abduce Y (vandalism) from X (design) would suggest that X is sufficient, or almost sufficient, but not necessary for Y
In contrast to deduction the premises do not guarantee the findings. Abduction is the intermediate between induction and deduction, which gives us the tools to describe and explain scientific creativity.
How can abduction be helped?
In Abductive, the presence of fear, uncertainty, genuine doubt or great pressure to act is a favorable “weather situation” for Abductive lighting to strike. Let the mind wander with no purpose. This unregulated mental game is called’ musement,’ a meditation game or day dreaming.
The three modes in detail
The terms “Fact,” “Rule” and “Case” are nicknames for the propositions that would be called the “conclusion” (C), “major premise” (MP) and “minor premise” (mp) respectively, in the simplest form of deductive syllogism.
Rule, law, major premise (MP)
Case, cause, minor premise (mp)
Fact, effect, conclusion
Deduction takes a Case, a mp of the form X => Y,
matches it with a Rule, a MP of the form Y => Z,
then adverts to a Fact, a C of the form X => Z.
All bachelors are unmarried males. Rule/MP
Hank Moody is a bachelor. Case/mp
Hank Moody is an unmarried male. Fact/conc.
Deduction allows deriving b as a consequence of a (deriving the consequences of what is assumed).
= applying a law, i.e., finding data to support an argument.
Induction takes a Case of the form X => Y,
matches it with a Fact of the form X => Z,
then adverts to a Rule of the form Y => Z.
90% of humans are right-handed.
Joe is a human.
Joe is probably right-handed.
Argument from analogy
Joe is tall, skinny and athletic.
Hank is tall and skinny.
Hank is possibly also athletic.
Induction allows inferring a from multiple instantiations of b when a entails b (inferring probable antecedents as a result of observing multiple consequents).
= inferring a law, i.e., finding an argument to explain some data.
Abduction takes a Fact of the form X => Z,
matches it with a Rule of the form Y => Z,
then adverts to a Case of the form X => Y.
The lawn is wet.
If it rained last night, then the lawn would be wet.
It rained last night.
Abduction allows inferring a as an explanation of b (inferring the precondition a from the consequence b).
= assuming a law, i.e., supplying a warrant that enables us to move from our data to our argument (i.e., a hypothesis, a warrant or backing, a condition).
Linking the three modes of thinking and how they are used in Architecture
Logical reasoning or inference in the building design, its representation and dissemination of architectural ideas has followed three forms of inference which are elaborated by Charles Sanders Peirce.
- Modern methodology is aligned with Deductive research
- Postmodern methodology is aligned with Inductive research
- Non modern methodology is aligned with Abductive research
Each one of these inference forms emerge various forms of designs:
- The absolute
- The codified
- The immanent
In Abductive reasoning which is the immanent is the negotiation of systems which are open and consisting of non-visual and visual information. The architecture or designer using a feedback of experiments and observations produces original and new work which is dependent but not determined by this system. Abductive architecture represents innovation and creativity.
Abduction as Hybrid
When we talk about a building, there are many elements which are the part of buildings. The primary elements in the building design Includes:
Design of the building
Heating, ventilation and air-conditioning (HVAC)
Building is dependent on all these elements otherwise it’s incomplete or useless. When we talk about Structure it is the Passive Control of the building and when we talk about HVAC (heating and cooling) of the building it is the Active control. So the building is not either totally dependent on structure or the HVAC. When these both things combine they form a Hybrid. That’s how Abduction can be elaborated just like hybrid. Abduction is also a hybrid of induction and deduction. When we do not have hypothesis we invent approximation, which is Abduction.
Deduction, induction and abduction
After discussing the view that induction identifies with all non-deductive reasoning, we turn next to the trichotomy of deductive, inductive and abductive reasoning proposed by the American philosopher Charles Sanders Peirce. (1839– 1914).
Peirce was an extremely proliﬁc scholar and essayist, yet just a small amount of his work got published amid his life. His gathered works [Peirce, 1958]2 in this way reﬂect, ﬁrst and foremost, the advancement of his reasoning, and ought to be drawn nearer with some consideration.
As for enlistment Peirce experienced a generous difference in his life amid the decade 1890– 1900[Fann,1970]. It is maybe reasonable to say that a large number of the present debates encompassing abduction appear to be owing to Peirce’s mind change. Underneath we will brieﬂy talk about the two his initial, syllogistic hypothesis, which can be viewed as a pre cursor to the present utilization of abduction in rationale programming and artiﬁcial insight, and his later, inferential hypothesis, in which abduction represents the theory generation part of logical thinking.
Peirce’s syllogistic hypothesis In Peirce’s days rationale was not so all around created as it is today, and his ﬁrst endeavor to order arguments (which he considers ‘the central business of the philosopher’ (2.619), pursues Aristotle in utilizing syllogisms.
The following syllogism is known as Barbara:
All the beans from this bag are white;
These beans are from this bag;
Therefore, these beans are white.
The thought is that this substantial argument represents a specific instantiation of a reasoning plan, and that any alternative instantiation represents to another argument that is valid. Syllogisms should hence be translated as argument blueprints. Two different syllogisms are gotten from Barbara in the event that we exchange in the conclusion (or Result, as Peirce calls it) with either the significant premise (the Rule) or the minor premise (the Case):
Case. —These beans are from this bag.
Result. —These beans are white.
Rule. —All the beans from this bag are white.
Rule. —All the beans from this bag are white.
Result. —These beans are white.
Case. —These beans are from this bag.
The ﬁrst of the set 2 syllogisms (inference of the rule from the case and the concluded result) can be perceived as what we called already a straight out inductive generalization, summing up from an example of beans to the number of beans in the bag. The kind of derivation exempliﬁed by the 2nd syllogism (inference of the case from the rule and the outcome) Peirce calls making a hypothesis or, brieﬂy, hypothesis – the term ‘abduction’ is presented just in his later hypothesis. Peirce subsequently touches classiﬁcation of inference (2.623):
Deductive or Analytic
Inference Synthetic Induction
My Hypothesis generation and hypothesis evaluation
I am now going to apply the hypothetical method and conjecture on energy efficiency testing.
How would I test it?
It will be a correlation of compactness of form and energy efficiency. To prove that hypothesis seen to be logical we need to measure form and then we need to measure energy efficiency. Compactness coefficient calculates the ratio of surface area and the volume. Greater the surface area, smaller the volume. Smaller the ratio the better It would be, because you have more volume.
For example, in Igloos the surface area is smaller so the heat loss is less as well.
How can energy efficiency be measured?
Energy Efficiency X area of the surface X U Value X Temperature difference inside and outside
The software will calculate the heat loss value for this. Now I know how to measure energy efficiency.
Taking 4 forms of different compactness ratio and calculating the heat gain or heat loss in each one. If higher the compactness ratio and higher the energy consumption, then higher the heat loss.
With some degree of certainty my hypothesis is confirmed.
COMPACTNESS AND HEATLOSS GRAPH
- Henry E. KyburgJr. Science and Reason, Oxford University Press, New York, 1990
- Harman, Gilbert H. “The inference to the best explanation.” The philosophical review 74, no. 1 (1965): 88-95.
- Flach, Peter A., and Antonis C. Kakas. “Abductive and inductive reasoning: background and issues.” In Abduction and Induction, pp. 1-27. Springer, Dordrecht, 2000.
- Fann, Kuang T. “Peirce’s theory of abduction. The Hague, Netherlands: Martinus Nijhoff.” (1970): 978-94.
- Dimopoulos, Yanis, and Antonis Kakas. “Abduction and inductive learning.” Advances in inductive logic programming (1996): 144-171.  Dinesen, Anne Marie. Charles Sanders Peirce-semiotik og pragmatisme. Gyldendal, 1994.
- Popper, Karl. The logic of scientific discovery. Routledge, 2005.
- Thagard, Paul and Cameron Shelley. “Abductive reasoning: Logic, visual thinking, and coherence.” Waterloo, Ontario: Philosophy Department, Univerisity of Waterloo, 1997. June 2, 2005.
- Sturm, Sean Kohingarara. “Category Archives: method.”
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