Enquiry Concerning Human Understanding Part I: What is Induction? The term inductive reasoning refers to reasoning that takes specific information and makes a broader generalization that is considered probable, allowing for the fact that the conclusion may not be accurate. An example of inductive reasoning is: All observed children like to play with Legos. All children, therefore, enjoy playing with Legos. Relying on inductive reasoning throughout everyday life is just a part of human nature. If someone were to take into consideration every plausible outcome of a given situation, they would never get anything done or been stricken with worry. The simple principle of induction (SPI) states that: “If every A observed so far has also been a B, and you have no special reason to think that the next A won’t be a B, then infer that the next A will be a B. If I have seen 1000 Labrador Retriever in a row at my pet salon, and I have no reason to think that the next dog will not be a Labrador, then I infer that the next dog will be a Labrador. Part II: The Problem of Induction We ca...
The first premise is: “All ravens are black.” This premise is a hypothesis that takes a general form -- “all Fs are G”. The hypothesis “All ravens are black” is logically equivalent to the hypothesis “All non-black things are non-ravens.” Logical equivalence can be defined as: “P being logically equivalent to Q,” which means that P and Q are true or false in all the same situations and that each one is a valid argument for the other. In any instance, anything that confirms one confirms the other. Confirmation Theory of Instance says if while testing a hypothesis in the form “All Fs are G”, a particular F (for some instance) is discovered to also be G, then this evidence is enough (at least to some degree) to favor the hypothesis.
Rene Descartes and David Hume lived in two completely different time periods, yet they shared interest in some of the same philosophical categories. Could animals reason? How did humans expand their knowledge compared to animals? Questions like these were answered both by Descartes and Hume even though they had two opposing views. Descartes was the first to address the questions about animal instincts, and later on Hume set out to refute some of his ideas.
Induction is an important cognitive ability in which inferences extend knowledge beyond the available information (Farrar, Raney, & Boyer, 1992). For instance, knowing an object belongs to a specific category can lead to beliefs that it shares additional properties with other category members. This can be crucial to learning and interacting with the world around us and can be considered one of the most basic functions of living creatures. Induction appears early in development (Sloutsky, Kloos, & Fisher, 2007). Preschool children have been shown to expect categories to promote induction and they use category membership to predict underlying similarities among objects – even when perceptual similarity would lead to a different prediction (Gelman, 1988). For example, a study conducted by Gelman and Markman with 3- and 4-year-olds, children were shown two objects, a tropical fish and a dolphin, and were taught a new fact about each that one breathes under water and the other pops up to breathe (Gelman, 1988). They were then shown a third object, a shark, and had to infer which of the facts about the first two objects would be applied to the new third object. However, the third object looked like the dolphin, but given the same category as the tropical fish.
Inferential statistics establish the methods for the analyses used for conclusions drawing conclusions beyond the immediate data alone concerning an experiment or study for a population built on general conditions or data collected from a sample (Jackson, 2012; Trochim & Donnelly, 2008). With inferential statistics, you are trying to reach conclusions that extend beyond the immediate data alone. For instance, we use inferential statistics to try to infer from the sample data what the population might think. A requisite for developing inferential statistics supports general linear models for sampling distribution of the outcome statistic; researchers use the related inferential statistics to determine confidence (Hopkins, Marshall, Batterham, & Hanin, 2009).
I will now examine another inductive argument which involves the statement “all observed emeralds are green” as the first premise and the Principle of Uniformity of Nature (PUN) as the second. According to the PUN, all unobserved instances in nature are like observed instances. Accordingly, the conclusion of the above argument would be “all emeralds are green”, which seems to be justified. Looking at the above argument, it is not surprising to believe that someone might think justifying the PUN would solve the problem of induction.
P1a – Of anything I clearly and distinctly understand, we can say that it is logically possible that it should exist as I understand it.
With inductive reasoning, jumping to conclusions is what the process calls for, but what Schulz is getting at is not the problem of jumping to conclusions; it is the problem of not overturning the false accusations of the assumption, thus creating stereotypes. Schulz expresses the frustration with the stubbornness behind stereotypes by exclaiming, “If the stereotypes we generate based on the small amount of evidence could be overturned by equally small amounts of counterevidence, this particular feature of inductive reasoning wouldn’t be terribly worrisome” (371). This problem that’s birthed from inductive reasoning is what Schulz wants us to “actively combat our inductive biases: to deliberately seek out evidence that challenges our beliefs, and to take seriously such evidence when we come across it”(373). Schulz wants us to challenge evidence when confronted rather than fall into the pitfalls of ignorant assumptions. Nearing the end of the chapter, Schulz warns that with attending to counterevidence is not hard, its conscious cultivation that’s the important key, without that key, “our strongest beliefs are determined by mere accidents of fate”(377). There is a threshold of new evidence above which our opinions would be amended, but what Schulz repeatedly brings us is that in many cases, that the threshold is not
In An Enquiry Concerning Human Understanding, David Hume begins by contrasting two aspects of human reasoning, which falls under moral philosophy, or the science of human nature (Hume 1). One aspect focuses on shaping human actions while the other focuses on reason. The first is easy and obvious and the other is abstruse and accurate. Hume shows that the easy and obvious philosophy appears more in common life; it allows humans to become more of what is considered virtuous and encourages sentiments. People who prefer the easy philosophy often think that it is more useful and acceptable than abstruse philosophy. In Section 1, he says that if the advocates for easy and obvious philosophy would cease to belittle abstruse and accurate philosophy, he would have no agreement and would leave it up to people to choose according to their personal desires. However, it is not the case and some advocates suggest that abstruse philosophy also referred to as “metaphysics,” be banished, and so Hume attempts to defend the abstruse philosophy.
Therefore, with every proposition we could possibly apprehend (whether true or not) each of their constituents are real entities with which we do have immediate acquaintance, so long as we can apprehend them.
Any hypothesis, Gould says, begins with the collection of facts. In this early stage of a theory development bad science leads nowhere, since it contains either little or contradicting evidence. On the other hand, Gould suggests, testable proposals are accepted temporarily, furthermore, new collected facts confirm a hypothesis. That is how good science works. It is self-correcting and self-developing with the flow of time: new information improves a good theory and makes it more precise. Finally, good hypotheses create logical relations to other subjects and contribute to their expansion.
Deductive reasoning is a concept focused on logical arguments. It uses arguments that conclusions’ typically follow from a premise. To draw a correct conclusion, the individual must assume the premises to be true without the use of previously learned knowledge to reason on the premises at hand. The individual will then declare a valid conclusion, which has to be logically correct, based on the truth of the premises. However, conclusions can still be incorrectly stated if a
The Intuitive Psychology is linked to the greater capacity exhibited by some people regarding their desires, motives, and beliefs of others, moreover being able to more accurately anticipate reactions as well as behaviours, an intuitive person is a person who has feelings or seemingly acquires knowledge about events, circumstances, or other information, mainly without ordinary sensory input or previous training.
During week three of this course, I was able to clearly identify the difference between Inductive arguments, and deductive argument. Deductive arguments consist of multiple premises generally assumed to be true, therefore, the conclusion must be true. However, in the inductive reasoning, the premises are all believed to be true, for the truth of the conclusion, but there’s always a possibility that the conclusion can either be true or false.
Inductive reasoning is logical reasoning where people have a lot of the information and use that to reach a conclusion. It is viewing the available data and figuring out what will be the results. For instance, from an online article, it demonstrates, “Inductive reasoning is a logical process in which multiple premises, all believed true or found true most of the time, are combined to obtain a specific conclusion” (Rouse, 2013). It shows that there are a lot of ideas to analyze and calculate what the possible outcomes will be. It can also be done by looking at patterns. When looking at patterns, it is important to study it to see what is recurring. This makes it possible to predict what will happen based on the knowledge that has been collected. Inductive reasoning is using information or events that have happened in the past to see what is in store for the future.
We can know some propositions in a particular subject area by intuition alone, or by deducting them from intuited propositions.