What is it called when we reason from specific evidence to general conclusions?
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Deductive reasoning is a logical process in which a conclusion is based on the concordance of multiple premises that are generally assumed to be true. Deductive reasoning is sometimes referred to as top-down logic. Show
Deductive reasoning relies on making logical premises and basing a conclusion around those premises. It does not rely on making inferences, then assuming those inferences to be true. Deductive reasoning is an important general skill for individuals of all types, because it will allow one to make an inference based on two or more pieces of information -- an inference which one can be relatively confident in. Deductive reasoning is also a propositional logic in artificial intelligence (AI). Even though, given various rules and facts, an AI could use deductive reasoning, common sense AI is still a challenge. Aristotle and deductive reasoning The Greek philosopher Aristotle, who is considered the father of deductive reasoning, wrote the following classic example: P1. All men are mortal. P2. Socrates is a man.
Aristotle’s example is called a syllogism. A syllogism uses deductive reasoning to arrive at a conclusion that is based on two or more propositions that are assumed to be true. This is also called a premise premise conclusion argument. The premises of Aristotle's logical argument -- that all men are mortal and that Socrates is a man -- are self-evidently true. Because the premises establish that Socrates is an individual in a group whose members are all mortal, the inescapable conclusion is that Socrates must likewise be mortal. To correctly counter the conclusion of this argument, one must be able to disprove one of the premises. Inductive vs. deductive reasoning While deductive reasoning proceeds from general premises to a specific conclusion, inductive reasoning proceeds from specific premises to a general conclusion. While deductive reasoning is top-down logic, inductive reasoning is sometimes referred to as bottom-up logic. Inductive reasoning relies on inferences made off of assumptions. For example, “the sun will rise tomorrow because the sun always rises in the morning.” Another example could be if a person has only ever seen white birds before, so they assume all birds are white. The conclusion of inductive reasoning is often based on the evidence given. This was last updated in October 2020 Continue Reading About deductive reasoning
Related Termsdata visualizationData visualization is the practice of translating information into a visual context, such as a map or graph, to make data easier ... See complete definitionMicrosoft Power BIMicrosoft Power BI is a business intelligence platform that provides nontechnical business users with tools for aggregating, ... See complete definitionnormal distributionA normal distribution is a type of continuous probability distribution in which most data points cluster toward the middle of the... See complete definitionWord of the Day learning experience platformA learning experience platform (LXP) is an AI-driven peer learning experience platform delivered using software as a service (SaaS). An inductive argument is an assertion that uses specific premises or observations to make a broader generalization. Inductive arguments, by their nature, possess some degree of uncertainty. They are used to show the likelihood that a conclusion drawn from known premises is true. Logic plays a big role in inductive arguments. In these arguments, the conclusion is supported by information that is known to be true or could be true in the future. Another way of saying this is that the truth of the premises supports the truth of the conclusion. The goal is to arrive at the most likely conclusion or the strongest possible explanation, given a set of circumstances and observations. Inductive arguments -- also known as reasoning by induction -- are assessed as strong or weak, rather than as valid or invalid. In a strong inductive argument, if the premises are true, it would be highly unlikely that the conclusion would be false. A strong inductive conclusion contains reliable beliefs that are backed by strong evidence (even though there is no guarantee that the beliefs are indisputable). But if an inductive argument is weak, the logic between the premises and the conclusion would be incorrect, indicating weak beliefs and a possible unsound conclusion. Inductive arguments vs. deductive argumentsBoth inductive and deductive arguments are based on logic, facts and evidence. Where they differ is that an inductive argument is a type of bottom-up logic because it aims to widen specific premises into a broader generalization. In contrast, a deductive argument is a top-down argument that produces an irrefutable conclusion (as long as its premises are true). When making an inductive argument, the arguer uses logic to establish a conclusion that is most likely to be valid, based on the given facts. But in a deductive argument, the arguer's goal is to provide a conclusion that guarantees the truth. Thus, the conclusion of a deductive argument is either true or false, provided that its premises are true. It cannot be partly valid or partly invalid, so there is no possibility of doubt. So, if the premises are known to be true, it's impossible for the conclusion of a deductive argument to be false. When the premises guarantee the conclusion, the deductive argument is said to be deductively valid or sound. In contrast, the conclusion of an inductive argument is evaluated using terms like strong or most likely. Inductive arguments with examplesThe following example illustrates how an inductive argument uses specific facts to make a broader conclusion:
 This is an example of a weak inductive argument because even though the premise is true (the observer saw only orange tigers on their trip), the conclusion cannot be true. This is because white tigers also exist, even though the observer didn't see them. It is possible to strengthen this inductive argument and its conclusion:
Although the conclusion is not 100% true (white tigers still do exist), it is much stronger than the previous argument due to the words most and probably. Applications of inductive reasoningAlmost everyone uses inductive reasoning every day to make sense of the world and to communicate their opinions and conclusions to others. Inductive arguments are also the foundation of scientific observations and research experiments. Scientists and researchers gather data, create hypotheses based on that data and then test their theories to prove or disprove those hypotheses. Inductive arguments are also used frequently and very effectively in academia and in the practice of law. In fact, lawyers almost always use inductive arguments and provide evidence that seems irrefutable to support those arguments. Their reasoning is aimed at establishing a logical relationship between known facts. They are able to draw a strong conclusion and support it with the available evidence. Depending on the strength of the lawyers' arguments and the validity of the evidence they present, the listener (such as the judge or jury) will assess which argument is sound and which one is unsound. These factors determine whether the defense or prosecution will win the case. Types of inductive reasoningThere are many types of inductive arguments, such as the following: Generalized reasoningA generalized inductive argument uses premises about a sample set to draw general conclusions about a larger population. The tiger example from the earlier section is an example of a generalized inductive argument. Example
Statistical generalizationIn this type of argument, statistics based on a large (and usually random) sample set are used to support conclusions. Since the statistics are quantifiable and not vague or unsupported, such generalizations usually strengthen the conclusion. Example
Causal inferenceA causal argument creates a causal (cause-and-effect) link between the premise and the conclusion. Example
Bayesian reasoningIn Bayesian reasoning, statistical reasoning -- simply put, probability -- is used to account for additional or new information. This kind of inductive argument is frequently used in statistics, as well as the following areas:
Analogical or analogous reasoningThe arguer concludes that because two groups have some shared property or similarity, they are also likely to share another property or similarity. Example
Predictive reasoningAs its name suggests, a predictive inductive argument involves making some prediction about the future. Thus, a conclusion is drawn based on previously known or past information. Example
Drawbacks of inductive argumentsAn inductive argument is not capable of delivering a binary, true-or-false conclusion. This is because such arguments are often based on circumstantial evidence and a limited number of samples. Because of this limitation, an inductive argument can be disproven by a single negative or weak sample. Inductive reasoning is also susceptible to failures because of cognitive bias, which occurs when the investigator only sees what they expect to support their argument. This may result in a weak argument or unsound conclusion and make the listener doubt the reliability of the arguer's beliefs. Inductive arguments can be convincing and show that a conclusion is likely to be true. However, they do not provide absolute proof. This was last updated in October 2022 Continue Reading About inductive argument
Related Termsdata visualizationData visualization is the practice of translating information into a visual context, such as a map or graph, to make data easier ... See complete definitionMicrosoft Power BIMicrosoft Power BI is a business intelligence platform that provides nontechnical business users with tools for aggregating, ... See complete definitionnormal distributionA normal distribution is a type of continuous probability distribution in which most data points cluster toward the middle of the... See complete definitionWord of the Day learning experience platformA learning experience platform (LXP) is an AI-driven peer learning experience platform delivered using software as a service (SaaS). What are the 4 types of reasoning?Four types of reasoning will be our focus here: deductive reasoning, inductive reasoning, abductive reasoning and reasoning by analogy.
What is the type of reasoning used to draw conclusions from evidence?Overview. Inductive reasoning is the process of drawing general conclusions based on many clues, or pieces of evidence. In science, inductive reasoning is used to draw general conclusions from evidence.
What is inductive vs deductive reasoning?Inductive reasoning is a bottom-up approach, while deductive reasoning is top-down. Inductive reasoning takes you from the specific to the general, while in deductive reasoning, you make inferences by going from general premises to specific conclusions.
Which type of reasoning relies on a collection of evidence to make a generalization?Inductive reasoning in science starts with observations, sees patterns in the observations, develops a hypothesis as a general description of the observations. Inductive reasoning does have its benefits. For example, it allows general conclusions to be drawn from specific observations in evidence.
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